{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "complicated-voluntary",
   "metadata": {},
   "source": [
    "# Rolling window features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "promotional-worcester",
   "metadata": {},
   "source": [
    "[Feature Engineering for Time Series Forecasting](https://www.trainindata.com/p/feature-engineering-for-forecasting)\n",
    "\n",
    "In this notebook, we demonstrate how to compute rolling window features (also known as rolling window statistics) using Pandas, Feature-engine, and sktime.\n",
    "\n",
    "\n",
    "## Data set synopsis\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "876b948e-2e7f-4321-9ff8-1b9734f4be6f",
   "metadata": {},
   "source": [
    "We will work with the hourly electricity demand dataset. It is the electricity demand for the state of Victora in Australia from 2002 to the start of 2015. \n",
    "\n",
    "For instructions on how to download, prepare, and store the dataset, refer to notebook number 4, in the folder \"01-Create-Datasets\" from this repo.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "hybrid-fever",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set_context(\"talk\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "confirmed-things",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "intended-logan",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\n",
    "    \"../Datasets/victoria_electricity_demand.csv\",\n",
    "    usecols=[\"demand\", \"temperature\", \"date_time\"],\n",
    "    index_col=[\"date_time\"],\n",
    "    parse_dates=[\"date_time\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d5252f36-7633-46f0-8f9b-d4707fac9330",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For this demo we will use a subset of the data\n",
    "data = data.loc[\"2010\":]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "functional-steal",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-01 00:00:00</th>\n",
       "      <td>8314.448682</td>\n",
       "      <td>21.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 01:00:00</th>\n",
       "      <td>8267.187296</td>\n",
       "      <td>22.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 02:00:00</th>\n",
       "      <td>7394.528444</td>\n",
       "      <td>22.150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 03:00:00</th>\n",
       "      <td>6952.047520</td>\n",
       "      <td>21.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 04:00:00</th>\n",
       "      <td>6867.199634</td>\n",
       "      <td>20.250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          demand  temperature\n",
       "date_time                                    \n",
       "2010-01-01 00:00:00  8314.448682       21.525\n",
       "2010-01-01 01:00:00  8267.187296       22.400\n",
       "2010-01-01 02:00:00  7394.528444       22.150\n",
       "2010-01-01 03:00:00  6952.047520       21.800\n",
       "2010-01-01 04:00:00  6867.199634       20.250"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7a758ba-9421-4be3-a9fd-23c1904a2d4f",
   "metadata": {},
   "source": [
    "# Plot data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "18390b5b-5071-49cc-9294-c3288304f951",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date_time'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[\"demand\"].plot(figsize=[12, 5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03852d45-a7a9-4931-b833-074c4f692b9a",
   "metadata": {},
   "source": [
    "That's a lot of data. Let's look at a smaller subset of the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a58bea99-c5c9-403a-bdeb-7d75a072dc1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date_time'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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sLE6dFCQssIeIxIRuYfgvviK7ulnOZxiGYRjGC/07Noz+3yyvqu/1s39eBSywHyBwl2cYhmEYxk+MOnUWroOFBfZMxIdnhk1sGIZhGIZxwigqlJenrBkHBCywZwheBWwWzBmGYRiG8YLfEeqc6j/QYYE9A1Hp37yFxTAMwzCMF4wyRHkA0jUL7BWwwB4i/OqXSh2cHwaGYRiGYRzYvqcYt385F2MXb445HqNhZ3kiUFhgTyI/zN2Y6ibEwc8XwzAMwzBOPPz9Qnwzaz0u/3BGzHGjVl0EoWH3vUY15q0vwOvjlgdyb6qwwJ4k9hSV4qbPZiflWpZmLoZDn01fG/3fbguLTWUYhmEYhgGAhRt3Wh4XNv9nCme8NgnP/boE1348M9VNYYE9WewrKQu0fpUH5d5v51ecl4lPGMMwDMMwvmGbEskgQwRhwx4067bvxatjlmHLrv2O5X5duNnx82SQ416ESRZ+9XWZeoQQIKKMXBEzDMMwDOMfZJOK3bgbH4S8HrQpyqBhk7F5VxF+WfgPRt3cN9BrJYqUhp2ImhDR00Q0jogKiUgQUX+Xcw4ior2Rst0sPs8joreJKJ+I9hDRWKtykbJnENEsItpPRGuJ6GEiiltsqNSZbOQS9nrvmKqdulzoryyyMwzDMAxjj50MIwLWsActomzeVQQAWLhxV7AX8gFZk5iOAO4G0BzAPMlzhgKwDKNPRFkARgG4AMCrAO4C0AjAeCJqayp7CoARALYDuCny/0MAXvRaZyqwW50a8U3DLlGmpKxcvjDDMAzDMAcsdiJMkAL1vd/Ow5LNhcFdwIEde4px/rApKbm2HbImMTMB1BdCbCOiswB851Q4on0/A8BzAO63KDIIQG8AZwshRkTO+RLAUgAPA7jYUHYogNkAThJClEXK7gJwLxG9IoRY5qHOpKCbnUiXT+BaxuuUlJZj0JuT0SSvKl69sHuk7tjayyIqdlunUxbkGYZhGIYBQDY69hinU5/lhs+mr/O3QgWe/30Jpq/enrLrWyGlYRdCFAohtsmUJaJsAC8DeA3AcptigwBsBDDScI18AF8COIuIKkXq6gKgC4C3dGE9whuRtp+rWmeyeGP8cnR/7HfMXVegt8X1nERstYznjpq/CTPW7MAPczdiS6G1I4WInuf5kgzDMAzDHMAYZY9Mii6XX1iU6ibEEUSUmGsANAPwmEOZ7gBmingJdTqAmgDaGcoBQEzgTyHERgDrDZ+r1BmFiAqc/gDUdrgHR579ZQkK9pbgmo+0UEAy3divrr63uDT6f7lu+WKqXP+aMufxYhiGYRgmCGxNYoz/ByxQJDMWepbphnu1rpu0a9vhq8BORHWhCeqPCCEKHIo2AbDJ4rh+rKmhHBzKNjW8l60zqejhHGWcMZIZJYadThmGYRiGkcFOVEhmptNkiivmBYqCdXNg+B3W8VEAWwAMcylXFYDVfsN+w+fGV7uy1TzUGUUIkefUyES17LEX86WI8qXsHUUiGnaW1xmGYRiGsWHBhp0Ozp/C4r/0x+x/aGfDn0x8E9iJ6BAA1wI4QwhR6lJ8H4AqFsdzDZ8bX+3K7jO8l60zJZTLCOyJ2LCrlo+eYJfplGEYhmGYA53TX51o+1l5jIY9WMkhmXKJWTwPg4bdT5OYJwHMArCIiFoRUSsA9SOfNSWiFoaym1Bh7mJEP7bRUA4OZTca3svWmVT0HzmZzhhyJjF6lJiAG8MwDMMwTEYSYxIT+LVSJ7CEQWD30ySmJYDDAKyy+GwUgM0AGkfezwHQm4jI5CTaC8BuVESXmRN5PRLaYgAAQERNocWEn2M4V7bOpKL/xnIadu/XiX1oKt7Y9TG9PelgEiOEwI2fzcaOPcUYfnlP5GQH4SvNMIwRIQQKi0pRKzepAbYYhkkjYpSRQduwB1u9I2EwifFT8rkVwNmmv1cjn90G4FJD2a+hOYGeqR8govoAzgMwUghRAgBCiIUAFgO4OhIuUuc6aEmZvlGtM9nodlBSYR396o4Wz4+5Zv1a6RCGad32fRg1bxMmr9iGMYu3pLo5DHNAcPtXc9H1kd/wV8hiETMMEx7slIWJ1xtfVzIVjOZLpZWGnYgeiPzbOfI6hIiOAVAghHhNCDHO4py8yL/jhBBzDB99DWAqgOFENBTAVgDXQ1tAPGKq5k4A3wP4lYi+AHAIgBuhxWZf6rHOpCPT0RLpjMbOZKwmv7AIjWrlxpXXr5UOJjHFZRUJc4tKLZPnho6d+0qwIn83urfIU0qexTBh4dtZGwAAd38zD2Nv75/axjAME0qCCutoJZukUsEYhnlcxSTGHFf98sjrGmhJkqQRQpQR0anQMqHeDC2Cy3QAFwshlpvK/khE50DLVvoqgHwAj5vbo1JnKghaYI8NrVTx5vRXJ+LJsw+1LW+n+Q+TqYyxjal/ZOQ4/oU/kF9YhJcv6IYzuzVLdXMYhmEYxndiEyf5h1XI6aTKJaZrhUH2kDaJEUKQzV8rh3M+jJSZY/HZDiHElUKI+kKI6kKIAUKIWRbVQAgxQgjRXQiRK4RoIYR42CoSjUqdyaLChj15JjHmS9333fw4wTxd46+HYJErhZ4l7f2JVi4dDMMwDJNZ+KthT08ZxYptu4tw33fzMXnF1oTqYe+9gKmIEuOO1/5ZuL8EO/epmehXRImxvmiYBOOYuPKhWOcqEKYvkmEYhmF8xChC+Clkh01eT2Qqf/Knxfh02loMfmdaQm1ggT1wtF9ZTsPujRNf/FO5ngqTGOvPwyRmGtuYbvJvVpq1lzlw2LJrP76asQ57i13SZoRs4mQYJjwYLQMyyiTGhNep/M3xK/DNrPW+tIEF9iQh1dE8dsZNO/fHvLe6VlyUGBeB/auZ67G/pMxbg3wmHSLZ2MHyOhNW/vXaRNz59Tw8MGJBzPEtu/bj4venR9+v27EXO/cmN8jW/pIynPX6JNzzzbykXpdhGDViZAgfJeoyC6/TpOazMV3Lq9PpM78s9qM5AFhgTxpJDesogX4tJ83/C78vtf0smcRo2FPXDE+EwbOcYazYvEvzs9Cjweg8OHIB/lyaH31fUiZw2KO/KSctWbd9LxZu3OmpbZ9NX4s56wrw+V/rUJwmkaEY5kAkqMRJllFiUqxhn7xiK+77bj627ylOSRtYYA+YZNiwx9VjcbXZawti3kcTJznU88Vf6/xpUIKwSQzD+EN5uXD1d1mzba/lcZXxqaSsHH2fHYfTXpmI5VsKVZoIANhbXLG7l847bAyT6RiVfn4K1JZx2P2rXhkiYPA70/DptLW4O0U7fyywB4xalBh/kHloou1xKFtUWjFpTlmxDTd8MgtrbSbzIBEmt9N0gjXsTJi4avgMHPa/37Bgg7rmW8WhbE9RhV38n0sTi4zAMEx4ibWI8U+kttawpzbXqc7EZakZ01hgD5iohl0qDnsSTWKiiZPsr2l8YC58ZypGzd+ESz+cbls+GaSb/JtmzWUyHD1T8NM/29tV2i0yb/l8DpZv2a18zUSf2Zs/m41lm9W19AzDJIHATGJSu7NmvnwYZA8W2JNEcjXsEteKlHEsafHhyvw93hqVAOlsw54VhqecyXg2FuzD4Hem4uuZ1tEI1m3fiyHvVYQU89ItR83fhAvenipV1m4I2rm3BKVlajbpvy7cjEHDpiidwzBMcoiJEhNwHPak5k0yXcyLeavfSlgW2JNE0JlOY+qRKBO1YXcoHBbb0Vgb9vQSgNOsuUya8tDIBZi8Yhvu+Gqu5ee3fD4bEyS3cZ267NbdRcpt0+tbvXUPDnv0N5z5+iT3c0yNUM0zwTBMcgjM6dRiXZ9ap1P1ydzKrCcRWGAPGF3DmkwNuwwyUWLCSLrJvyywMwCwYMNO3PDJLCz+Z1cg9W8o2O/4+cqtyd0ZsxpV3p24EgCwcGMw3wHDMMknOBt2ifjUSURlLi8vF9qfz/JVjq+1MXHov7FcHHZ/flwpp9PI6tWpaFhkeWOnTzcBmE1iGAA4/dWJAIDfF23G0idO8b3+HMX9Wlltu1dEzDOrtU1FQ5V2GY0Z5gAlKDnB2iQmdUKJcSp3akdpWXl0vP/u+j6+toEF9oChFGjY5a4VsWF3KBsSeT2tBXbmwEII4Wi2Vaxov+0XyV58J3o5fs4ZJj0IyobdUsGexHEsLnGSpBLhr9U7sPgfzUl+xprtvraJTWKShIwtUzJt2KNRYhwaFhZzGWMT00HzZvxOWcN+4HD31/NwzDPjXO289xXbZxDevqcY705YiU0790WPfTVjHS56dxo273I2e9Hp++xYzwmLAH+EZatF9kdT1yReMcMwoSLWhj1Yk5iUSiSS46JRCWqVrTURWGAPAGExWSUz06nMtfSHIR1MYlIbe1WdMmEU2FPYECapfDFjHTYU7MOrY5bFHDc7TP4wb6NtHTd8MguPj/ob574xOXrszq/nYeLyrbj/u/lS7Vi3fR+u+3iWQsv9J9FHVvWxKSkr931yZBjGHeNT5+cjGLbHWXZMEjb/6zz24yLPbWCBPQBiNMKpyHSqoM0P20NhRVmsij30lFvY7zIHDkWlsWYv1340M+a9067WlJXbAAAbd8Zr09dul09aVrA3NamzdWKeAQ/nqzw2e4tLceyz43DW65Mcv1uGYdRxVZgFlOnUUsOeQuWd1Vy+Ztse7C+J3TE1NtFKOH9v4irs2ONtfGaBPQCMAqZuwiEzkbj1xUnLt0olEFHJdJoO2us0k9djwlGlQ3uZYNGFcB1ZYVTl2Ux0XehkpuMFt+HOy7hzwyezLMfRn+f/g00792P+hp1Yv2OfxZkMw3jF2pa84qDxkXzml8WYZhrvvGL1rKcyDjuZPpuwLB/9nhuPM1+LDVNrtJSwy1tT6lGxwAJ7AFjZb0rZsDt8NnPNDvzn3Wk44cU/XSc7GdMavURY7NSdMN5v+FsbaxLDGnbGK8e/8AcK91eY06g8qqr97qinxqCotCxyrtKpcewpKsXP8zc5ljnmmXGYqeiQNWr+JvyxND/uODulM0xwWA07MXbrpoHp3xbJ1SYsy8fkFWqRqaxkppTGYTeNLa9ETB+XmJSoMm30Ok6xwB4AxglEdzpUyT5qxYRlFROVm62mnEmMrmF3L5tqymJGh9S1Q5aYHRYWIBgTso7TK/L34P8mrw62MRF27ivB4k3uu3d2fDx1Dfo/Nw4LN+7ELZ/PweOj/q740OIh2FCwD+e/pU3sVpo0u+9od1GpYzvu+npeYLHuGUaVPS79NR1wc/50m5K1LMvTMfidadhSKOc4b3/dFJrESJYLsoUssAeA5cowwTqzDZOe23aKjDa/XAA/zd+Ep35enGDLvLN8SyF27XfPYGi8n3TYEYiNEpPChjDhRKFPFJcmPwzk0s27lc95YMQCrN62F1cPn4nRf2+O+czudsvKBe74ai4Oe/Q3fDptbcxnI+dusDzH7emfsnIbTn5pgmSrGSY4flmwCYc+8iteH7c81U1JCDeTGLcpeUV+xXiyQcFkLdWJk7y6w6gE/VCFBfYAiIkSE3mVio3uUCTLIPmVuMRyljKJEcD1n6QuksSstTtw/At/YsBz413LlisMDmEgxiSGrdgPCJTszVUqNizUra5gp8EzK7Vl2yeESGiRsF3RmerrmetRuL8U95ki4CzYIK8lT4MhgTkAufbjWSgXwHO/Lkl1UxIiUQ273XmuZUP2YPtp3lrucYhlgT0ArFZmcjbs9oWMfcUPkxiVFd63s9ZLl5Xls4hGbdueYtf7MWqsZdo9beU2S1vXZME2tZnP5OVbMeS9aViwYScmLtuK7o/9Ln3unV/PwxiTFtoLY/7ejEMf+RUvjV7qy+Qm4EM4Rov+7uczMGL2Bql49K+OWZYWDvUMk4442bDLnudG6uOwx16NbD9xOssa1rCHCZctJNvTHIrEPiBu9SQekUZnwrJ83Pbl3JhjfsQ7rlO9cvT/PcXOdn7Gy7ldeceeYvz77am45P3pWJmvvrXvB8bVc6YmTtq5r+SAFogGvzsNE5ZtxemvTsRF701DwV530y4jV/zfDKlyxt5jHuSv+L8ZKBfAS6OXYf4G74mSEqGsXOCLv9a6F/SJsYu34JSXTSYvFt3w+d+XYvTfW5LTKCYt+HTaWlzz0QwpM0ymAidb8tGLNsf6q1gQq5mWnzOs5IykZjr1ei2J87zKUCywB4CVplzKEVSyfrfVmVxWVbmrzVyzI+7Y4HfivcATwa0pKiYxmwzxq5dKhMAMghgn2QyU1yev2IrD/vcb7v5mXqqbEjibd+3Hmm3WobmSgXGuW5m/B9d8JCfom9m1X875TWZUGDWvIgLMp9PW4O5vKsxZktHdZc1uVm1NzYKdCSf3fTcfvy7cjJdHL3MvzESxtmHXXq8c7m08ksHaFzB5ErvblexkEZk2soY9RFibxCQWJcatftVryS7wrKqatmq7r9pV1zCVMQK7S1nDw5KqkIpGE54MlNdxe2TH5csZ65VtltOF7XuKMeyPFej15Bj0e248NhTIO0vJdrt+z43Dpp3O9Zp9IH5dKGdKY3xMzIk9nM9zf65v+HRWNB/E2MXuWuyg/TjsJki/hqhtu4vw+I+LMG99gT8VMilFxfGR8TvQg/xYYDUWbdsd7HwzVTKGvNNdyHxdgWrYiagJET1NROOIqJCIBBH1N5WpR0R3EtEEIsonogIimkJE59nUmUdEb0fK7iGisUTUzabsGUQ0i4j2E9FaInqYiHISqTNIrDpaonHYY8s5C7By2nxJJzSb4+ZsjjolZeXK2Qbdiht9bFVWvakSlq3CemYqhz/2u3I87XTguo9n4mlDBCUVm3PZ+W3Ntr14/MeK7WSrZ/njaWss6ne/wM59JfhlgaYJ36GQ9VT2yV0RSQgisygO4hGw2vkLgvFLtuCIx0fj3YmrcMZrkzDkvWnYuY9NKtKZTBmSP5qyGlcPnxGTqyEIrMYEFRk+JgiHwndvJRec/upE3xIzWXHB21ORX1gEwH2ctbsXv30Ijchq2DsCuBtAcwB2++BHA3gCwDYAjwO4H8A+AF8S0YPGgkSUBWAUgAsAvArgLgCNAIwnoramsqcAGAFgO4CbIv8/BOBFr3UGjXUHT0xitwujZFWtnxp2u95npbXbW1yK/s+Nx9lvTFLSwLub+Mg7nRo/TpWwHJOZNUMmByfcbBjTkWmrYhchQdlOGuOKm68JIDp5GJF9dq/9eBZ2F5UG+hyYa7YS4IO4+rlvTo7+b781nRg795bg0g/+ijk2YdlWvPj70gRrZlJJpozJD45ciN8WbcarY4MNGyksdHMqpilelWh2c/3D3y9UqEWd9Tv2AogfP4zvE+1DLoH+bInTUtswE0B9IcQ2IjoLwHcWZRYCaC+EiKqEiOgNAKMB3EtEQ4UQ+l7UIAC9AZwthBgRKfslgKUAHgZwsaHeoQBmAzhJCFEWKbsrUucrQohlHuoMFKuOJhcb3b6Q8aMYm26LsjLbLbIrPLtSe4vLkFct9tioeZuwoWBf9K95nWrWJyu2RcWG3Wg/npUig6+yDDaJee7XxTF+AkD4wm8lyvIt8bbPSmEbPf7oOyTNi7S2yF1kb1GpUntUf8t0FH5WbdV2B1rXr+5Ybtue+MUSAFczJibcZFqo3Y0K5npesHQ69Tjmq5ip2skFlXOCndj16dt8eenQuFLXCFDDLoQoFEI47kMIIVYZhfXIMQFNI14VQCvDR4MAbAQw0lA2H8CXAM4iokoAQERdAHQB8JYurEd4I9L2c1XrTAqWThoSNuyy1dsI7xXHZCqRu5Zdx9pbHK9hNwqqblo9lcQLbguUmHYZNJa5lbJdSgdD7BZg5kwO+0vK8Pq4FXHH56wrwMg51olu0o3Nu/bj+Bf+SNr1ikvLo/1Ftq+oWJwJxCZdcy8vV7ldlVaHg34EVKa+7XuKMWDoeAwYOt51gWRX76ad+5X8ApiQkTlDMoDg5xhLiwGl870psOzkgkrZQQvsNj4xhv+dFn0ysl6Yo8Q0jrxuNRzrDmCmiL+z6QBqAmhnKAcAMa7IQoiNANYbPlepM3Csfgq5yC1ydbppnOVMYiRXizbFLEMuGf53G0PcFh1GjGES3R6GEkO7qgS8ErdiS+F+XPPRzOj7TJobnAaZWz6fk7yGBMisJNlG60xZuS2awEw2K66qdkZlQldX/KRXD1/8T0VCpiUeo0jNW78Tp5pDSybAj/M24tIPpgeuKWU0UulXNG3lNjzy/cK08oOw1rArmLx6NP+wm28qZQf7++k+eHEmMZK3nHINu1eIqC6AKwGMj2i7dZoA2GRxin6sqaEcHMo2NbyXrdPYvgKnPwC1re7LDSvti1T2UVlHUBdhV2b1lmjnc9smU9l2VIl6o6KNT4V2+75v52PlVkMYwPSSZ6LkFxa5ZtRNB4pKy7B2214s3VyIbbs1E4eHRi7AVcNn+JJPwA9+XvAPACBbVmIPEXGPmMUtlAtIJTL7ZuZ6T9GnbG3YLY4bxyX3fBb2n8U84wly46ezMX5JPno/PRYfTlrlW72MNal8yv799lR8OHk17vExJG7Q92MZ1lHlfMP/KoKqXdmgNey6Wa15LJJVSAYZJUbWhl2ZiBPoJ9CE3ptNH1cFYGUguN/wufHVrqzRSFq2zkBZvmW35ZZ6whp2FY10EjTsTskUALVtcPewjtbXsGxXioWwxf/Eau3S0V5ywYadOP3ViTikWS38eFPfVDcnIYa8Ox3TV1c4c06/byCGT9Es935b+A9OObSJ3akxJKNXyWr+VCY9IdS0YbKQ6VWn0CLee6XsLFzy/nTXOm//ai5q5ubgxIMbu5aV4ZlfFqNhzSo494jm0WPGr9j9e0n+WPLID4twfo8WqFY5sKn5gCQm1G4IhuQJy7a6F5IkcJMzq7leQZdjPF/JnM+mbE7Aig2vOwIV+Cd/mQlyqfIqgJMAXCaEmG/6bB+AKhbn5Bo+N77alTXuIcrWGUUIkef0B0A5feD/frD2YPYz+6i7DbtMh5G8lk3n+3PpVuw1ZShVCvWkcJ7RkdTtYTKuXFPhDGm+ZhgmB1Vei0QdWLBhV8zxcOij1TAK60Cs70VhUbxwmcrfS/baqmtSJW2YYt2/LXIPd6myYPhrtXqIUKdF/O1fxWZpNi6Kwtqf91n4BzGJYZxDwjAk+znOBK5htzymoDRwrc2aVDmd6r+NV6dTuQAjio2KEMidE9HDAK4HcJcQ4jOLIptQYe5iRD+20VAODmU3Gt7L1hkodlsdiSYfMD4gbiYik5bLxClNzCbmmV8W48ZPZ9sW9WPry+pzt1pjv5vkT8nma6ahlYMt7r4GqRGBhBC455t5uP3Lua6/eUwW2oCa++PcTViZr55lU1bDrtqv5RUBQmkilt3WVWmuShcqUIgvrxOrYXcum6roR8UZYIoWNlQCIiSDMLRBlkSjxMQqGFWua308aJMYHfNYGGMSYyp74dtTo34JMuNiaJxOiegGAI8AeFEIMdSm2BwAR1C8kXEvALsBLDeUA4AjTddoCi0m/BzDYdk6A0XFnjK+jH0hu07vdSEgr2G3x5zlUCXyi0pbVO7XWDYV822ZqX3paBJjHKge/WERtkZsv922Qf3NiCfPok278Plf6/DNrPWYtbbAsezI2d6i2RhvzS1RSWFRKY57Xj3SjLxJjHydWwr3K00Oas+tpMDuMWazGy94iIdu/Ibd2uVqMONDf19tYQufqoVCJhPTV5MwJN9h2tl5+ufFMb5tiSpykhmJLFEbdmNpP8aXwDXsAO7/bn6c4jPWrIpi7mXKym149hct0Z6UhUMYBHYi+jeAV6DZrt/uUPRraE6gZxrOrQ/gPAAjhRAlACCEWAhgMYCricgYo+86AOUAvlGtM2jsJgE/M53GPADS55hqkDxRpWOp2NnHXENFc+sq3BvNZ5I/85kvmUaKFEven7QqOvm4+g+YPn593HJc9sH0wLf4jfWbzbTMvOJDkpH3Jq5KuA4rZCdxFUHxjNcm4ainxkiXl62ZSH4pqhaGUmD22h1SZfU05eMWuzu06hifx0SHh0QF6z+X5qP/0PGJVRJypqzYhms/mmm5MEkmsbkxgh+Uv565Pub9sD9W4O0/V0bfJ6phj0nO51I20YVlolFiPMsFNg9o5YA17ALAJ9PWxh13U3xs3qW5S8rco1mxJ4u0ZwsRPRD5t3PkdQgRHQOgQAjxGhH1BDAcWqbTMQD+Y1r5/S6E0A0evwYwFcBwIhoKLeTj9dAWEI+YLn0ngO8B/EpEXwA4BMCN0GKzG1UsKnUGhoqTpuy58XUZzvG4e5po4iTLsh417G4Pf6xJjIvJg+HLSYWFhvle0k1gf2LUIvy6MNYuedJyzUFKJZoPADz36xIAmtB/w4DkRFVNhnZyj4Xte6KUlwtc8/FM94II7h5Vq5Utr7p9fvYbk90LoqK/jf7b3Y6+AmOUGBcNu0u7/1iWjwEdGypcO5ZXxy5zL5TmXPjOVADAgo07MfHu4wK5xvode3HZB3/hzG5NceNx7S3LGH2fUuGkCQDzN1S4xCWqFS+TlNjXbNuD84ZNwZndmuL+07p4ulYqosQUlZZh3JItlp+lKg57TAQ6WPUj7YCM02oyTGIei/wNjry/PPL+jsj7LgAqA2gA4H0AH5n+dEEfkSRIp0JLanQzgOcA5AMYIISIUYEJIX4EcA6AetAcWc8B8DhMkWdU6gwSu59BLnGSg0mM4X8VAdaORKPEWJZVqF/Frq1cqWzi300ipPt29jsT7LXHKr+pke9mb8CWXfutP0yQn+dvwqBhU3ys0Xr2W56/O7qlHYT96eQV2ywjrFgRlOmREMKz5syJ+74zxxzwBy/fg/Gnu/SDv/Dd7PW2Zd3Gj8s++Ev5+jFtselraT6EWLJ+R3Ax5h/5fiGWbdmNob/Zm0jFZMAOWGC3m6OMCcwSaUNRaRm++KtCA+y0Y/DEqL+xpbDIcVx3w1JgV+ikZR7sVJ//bSm+nGH9bAYtsNvd2+i/rRcQOvrPK6M99zqES9+5EIJs/lpFPv/QoQwJIcab6tshhLhSCFFfCFFdCDFACDHL5tojhBDdhRC5QogWQoiHhRBxs5tKnYFh80PI2bDLfRibSEiuWV7xan/qJljbOdGa2ba7CJ9Nrxic3O63pMyblt8vzPeS7gI8UDEhuAlIRaXWpi/Lt+zG0U+P9b1dAHDdJ94f71Xb9qBU0sHv02lrcfNnswEEYzPqZspjJKidIyFSLyyqhqxUxfzL3frFXMtyXuv3g1Q4y6cz210y1gLJNYmx68PGPAuJLPrfGLcCD46siEbnVFVRaeIOzG4hnFXOlx27jOZDZirlpOb3c0P/edM90ykDf23YZYVd5/b4r2GPfTBVbNXsP7v4/elYvqUi4oZbvYmEdcwvLMLYxZulhTgrzL9zRs29LvfS7dHfMcbGPCFZSYpUrvLm+BUxWWnd0EMYBqGhU8pGChGMWY4A9kv6GxBSs4NlJOgulWifLSotw02fzca7E2yED5ufPKPGjJAQm1AvedcyYrxuImPIyDmxjvOpCOuo8uj7veudnQIn2zgsmqAvBGXEhzIhMGn5VpzzxiTMXCMfypYFdp+J65CRHzZRG3bjR35EpgtiUohpl5IpjX3hhRvVYoGXxtiwq93kiS/+gcs/nJGQU6H5mqmKnBIEMvLLFf83I/iGOPDD3I3RjKYyjDFFOpKZC4LISKpqiiKTOdRLG/o+O06pHf63QaWsXOFdhqg+Vguj84dNsVwAJXp/H09dix/mbsTjo/62/NyuF2XSmGGktKwck5Zvjfk9kkWMhj1wG3br48ZxI5FduiyF8cePvmStYZfHKMD6scgO+umQWVRY/QJZEWlaNkrMf96dhllrC3Dum/ImnSyw+0zcbyX04zLdzL6Mnad14GEdVQSJmPBN8vbOKrfw4IgFjuYDZYbRQfWb2bFXm0j0TJieMF30q5nrMd7GeSZM/L1pFy62y0apsOhMBs//tgSnvTLBciv865nrcZ6vNu3xBGESoxafWCC3kv9Dd7nwZws9Wch+ZYMjjo+A9UQ7ffV2DBg6Pu54ov3d6LcRhG9AuvHq2OX4z7vTcOHbU90LKyDzdcXulqTIJMZow57A42tuvdNw5EdfStSG3Q95xa6+IJBxGrWaA7IjP2qQUWJYYPcZu59BSlyXFqIVK7ZAttN7TSWsKoCo8KlFyCWdRDTsOonIY1bXvDRB57Rk8OrYZfjTRWurZl8c3KD66tjlWLhxF575ebHl5ysTCCE3fZX79mQQJjHXSkaIAbTnLIhFQ7rZTsu215ixd8nmQssyWwqLMG1lbNxlr5OqTk52xW9UajEg2tUeloWx37w8RouKY941TQbG71Tm+f114T8xvlNq17I+nuWTDbu5ezjZ5PvRl6yeMyUbdr+To/j4eFjfmzdysvQoMRICO9uwh4O4DqBrJyV+IGOJ2Wt32GpmvThxOF7MJ4xVqsVhV7uOUzSNWBt2jw9FAoNpipJ9JkRxaTl+mv+P7ef6t6FmrpBYm2T4YsY63+uUMYdS6R+yMcVVKBciEB3h4HenSZclCsgkRsmZTb3+u76eZ/vZ/35YhL9Wb4+O1YkuYIwa1RIrw1ab6tNwCAk9KiYxe4pKcc1HM3Hvt/PjFnEySGnYE5pjYut3qsoXgd3qmEK1ZTHySrg07FZVeRamIz9EmcTpgUeJYeSI+x0iB6ScTiO/4p6iUpz9xmRc+sFfWBrRCMU6mhqr92oSI3ee9ygxKhOv2j3st4lGApg07B539xPRoIZJO7ZtdxFeHbMMa7bZa5zLygUGvjBeqj41v4R4Lnh7CtZt3+tQv8DMNTuwpXA/ikvLcdXwGdHscWFCpX8sMzhM+4UQ4UhtvlXBV0CWRPtYIizatAvnDZuCT6ZpJnEJL74Nv5H5vu79dh6mr7bezQnzTkdxaTk+nLQK89YXBHqd3UWleOH3pVLXkfm6YmNoOz87xQazMC+7AXa5UYxmMInt4gZT1r6OxLTQKmGZZfDz8bC6NxmB3er30zXsHCUmA5ByOo28bjbYPi7cqCVbiLX5TlzDLm/DLl9nrA27wnmKT2BRib0kXmoM66hUawUqTj1mwjTVXv/JLDz/+1Kc8vIE2zKrtu7Buu3OMZL1wWnyiq3S17bq71NXbsftppTdRsYvzce5b05GzyfG4Kf5m/D7os14Y/wK7A4gIkoiqPSPKgGk0RYicXMNP9qg4qAqXa9SG7TS7RrW8LUNb45fASDxKDHGXmJ+Hj6bbr87FOZdus+mr8UjPyzCGa9NCvQ6T4xahFfGLPPtOmUKiZOMz5aXPmA/1/ujYTe3ydmG3Q+TmMTqLfdh1zvm2gnXUIHVz1sqqekz30p2th4lRkJgN538leRuMQvsPhPXHxWeS/3cfSUVGuSqlbLjy8WcE6yG3SpFrx2yGvbpq7bjw8mrDWWlLwEA0QQ2VpQZHjZjG9Zu24tCyegEidkXhme2nRaxx97rGKpPYiEZKXLPt/IJcOy+BicNuzGdd6FBSN8nGWowWaj0jyDSaBeXlSectCdRPv/Lf3MkwJv2zO+9Bn08khkjFxiyVzqhcls/ztsUukWqjsqiPRHGLfY3CpJRiHJ7fo1KHy8LY/t+Y9Tye0dJWA5Kw65iEuNz9nE/d7E9a9gtjukadit/lbjrmsrc+fU8nPHaRNfxhAV2n7H7qeTCOmpljFtyelYv49mxK1blJkq3RxXjQOJU/flvxUbxkLHvN+IUyaLUYjW/aOMuHPvcOPR6coxU/YnEefUyIG0p3I+Ppq5BwV73BCBeGTlng7WDjUR7vXwd38yyzlJnd73xS7Zg1LxNFdc0nhOqfQs1k5jKAWjY9V23VDLaJt5+shk+ZbWU2ZGKAKyPjTIRc5wcyo3PjZ2ZhBWvjFmG/34+W/6EJJKTSHgTBfzeQVKxYTdqWL1p2N3LJKQUUqgrJga6x+/UzygxfujH/ewaVnXJCNxAfD/Sf4dSCSN2q/49b/1OnP7qRMfzWGD3G5vepJI4ySiw5+gCu40dmNfOWyLjGaGIdxt2tevYZdQsLSvHnHUFcfV+GdluctY0V5CIfaGXQfHCt6fiwRELcPPncwCoCRey3PL5HNfUynYQCPmFavbK9ypo44F4weeBEQsq3iRJXpfVlqpMtlVy4nfIEuWVSLSNA52ycoGHDBkfnXhOwRdC7275u9z7vNGOf09RKbYUVpgzGm2lB74wXilBitdnNUheH7cco+Zvci/oA2rhhN0xCkhuNuxGgUtVmQTYt914OJE5xryIcBqPhA+ygqXA7jHTqR9hY/3cxfaqYbdCj7NfJmFS43WngQV2n0lEw66fbOzU0QgdhpovfGdqNBunV025ZdSCBInZBVBoluoDuN/Ghv3BkQsxeUWFV7/+3ag+gIkkxvHyIK7I15xC/1yaj7GLN6PrI7/i+d+WeG6DHVcNnxFnKyfb3Cv/L3UmGMnSr7tpN3RUQioaQ/v5hd5fMhGVqDrGZ92NeZKLMaBiPFJKUFMu0POJ0ej5xBh8NWMdthTux4aCCvOvrbuLowlSwmQ2p8Jzv/o/Jtnhd2bkWJMY57KlCZpw2J1j/Nn9jETmdD+x/m7+mc+qmcRU/H/L53OwKoGwu4C/84FVLg8ZDbvVHJCISYwsLLD7jF1HVpDXYzTs+sNiPn/W2oKYc1QpDUJgj1nN+6shMWJnw26Om6s/E6rbq6mMwHH5hzNQLrRY40FwpymsnewgPne9P2YYXsxbwhR5BwCmSoZ6KyotwwU+J4nJdBb/Yx0nPVG8RNZw8pUxU1xWjj2RHbw7v56Hnk+MwZczrM3CkulUGuTiIMi6lQR2xagcbgsxo0mMF92N3XhlVJIlYllk/t6dFAjFPgRhsDpPpS7z9zE0QWWUX93un537LR3nyyRkI6tvPFtBYOcoMSHBTiCRGdz0MkYNu36a+QfW33vXsAdgEmMTetIN1XuQtTET0cWOosAeRGYcG2S9w1OJn+uXzbuKsERRKPM6QBvNo/xi2spt+H2RnP32yDkbfb8+4w0vwqXK9r1XJ7wgGTVvE7o9+nuMb4ifBHkbXkMX2v3OMTbsLvUZTWK8zAV2Tf929oaKepMQh/2pn/7G35sqwlL6q2FXMIkx/5gJ9hu/FDh2c6+8fBH7Pqphl5CtvN4DC+xJQsWG3Wijrf+w5h/YTvMui2zoIhVi462q2LgpXsfihNfHxWuko9+d4VZlBppkyevjl2yJ03gnG6mdH58n5pNe+jNmh8ftN/E6uD36g5x9swpjbZKZWRG26DYHMmXlAt/MtNZ4m9H7o4qG3atNb1BsLNiHGz6dhZ37SnDDp7MCuUaQCw+VumUURTEJ9VzqM2rCzeaR23YXYb7LbqOMuYNqpuJ9xWUYPmU1Vm3dI23D/tafK2Pe+2vDLo95hzvRULd+9TqZvmKH1VeepWDD7vXZyfF0FmNLQiYxkTJFMSYx1ufrq0Cv25JWtluJ4tVeLlEN+/Ituy3tK/XnxjhgCGH9sBkH2WSZxMxas0P5nB17ivHTgk04+eDGqFejSsJtkPnq7Zx8E6G4rDzqUO02dnmdaIKIaOHmsGYkbKY8BzLlAo45AKwoUhHYA9xRtL6eVoeV4LcifzcGPv9HzLH8wiI0qOl9vNhQEJ+rIcj+rWLGaA52kG3xjMZk23QYcP7etAtnvzE5+t6svDnrjUlYt30fPrysB/p3bOjaHjtUlULP/LI4Ggq5RpVYsU22Lq+/l9foYhXXjX1fkuBCz69uZ/d9SGvYTe9fGr0MhzarLXV/7HQaEuw6k1zipIhJTEm8ht28Ioumz/bSSDgn7vDChoJ9+MIQm/mHuZtibPGdUF10mL8Lu3CIVrsTdlcyDuiJhHVUwcvAdc1HM3H/dwsw5L3pShpAO2T6ZdA7+G6//3WfzPRk3hKEw+e6HfZx5M2wvB4evPjUfDNrg2M5I0HuKJopLi3HyS9NwL/fmmopfH5pESO/xxOjscWQkE+VM1+Ld8guKxf4cd5G29jssnkvrFBxyjN+9XaaS2N9Szbbm+Td+sWcmPdm5Y2eZM4pnKdMX1BVCo2cU9EXVaLEGPGsYVc4aoX5t/xhbmKmgn75Ttj9TjLabyGs23HF/81AGZvEpA92P4OcDbv2GmvDHhHYTefrq8CwaPGOf/4PbDGE/vts+lo8PmqR1Lmq1jmqNmYy4SaND+n01dvxk8/hy6x+f1XH30Ubd0XTmS/atAu9nx6Lnfu8T4phwe3nXLBhF856XT3jYSLRfuxQsQcOItIPEzz6o2qlVbZDRQh3Sh4mw/glW7BkcyGmr95uGYPert//avK9WPJPIUbO2SAlHG/dHa8UOfWVCbjx09kY/M60OPOv/MIidH/0d9d67VCZ14wl7U4zzhkTlm3Fbwv/sSznR0hdOYHde/1mWUDWvMazDbtF/1Dp737H1A9cwy45L9s1g51O0wg7wVzNht3C6dS0atPtpEIir8dkZ9UZPmWN1LmqA4mMjZixXqNNouw22PWf+Gv3aXVZN8ff016ZEDVdWrttL059ZULM59v3FCfstGp0SkomMouoREn1YnYP27CHhqC7gorW7z/vTkvsWob/rcLz2mlczUdPeulP3PL5HIycuwETluVj6+4ipV27NdsqFh6FRbGKgy9nrJNWrFjhNSywlXA4d10Brho+I+bYS6OtcxmYT/cyhsi0XcWG/af5m7Bjb8X36zUk4KM/LPJk3mh1tXIh8NpYuXwQfo/DftVnV02xZEAOu/PtkgYaYYE95Eg5JUWKFFvYsIddw54Iqn1XtrPrxUrK4hdAcXVKPqQLNuxErydH4/gX/kC/58ZJRzyx+p3cHH8XbtyFl0cvBQBMXSUfc1qFVDm9xmbgkz9PRaBYsSVz45Uzaqg4heoC4DHt6kufozIBJ+o/lGNQz1pd125OsJMRb/1iLoa8Nx1HPj4a3R79TTqBmBHzJVMVa37or0viFjFXWOSQ2C8puNpFoKmcbS86ydz7nHUFUk7pGwv2xSmPzLKAbN/+auZ6S3MpN6z604SlWzH0t6Vy55v6aN3qlZXbYMSvnmX3yMqY8ibaBjaJCSuR30VOwx4vhJcLga9mrMPXpggH+kAdZnn90Ga1pcqpDu6yc6P+PVrFtTcjGzXn6Z8XY/OuIizfshtrtu3FuW9Odj8J1pofmYGhUN+iDfHv7IUiid/Eitck49NPXbkN/yRgs8tkFl7GyepV5LPUJiu2+r7iMsyNyeacmLmCmf0l5Z4W8fFRzLy3IZFrfzh5NT4y7exaLZB27bM2fbGLxgbE7sJWqWQvOsnce3FpOTo/9ItruU07482y4hdH7tfTsTKhcsWi/pUKyY/M30ftqpXU22Bsjk99y07ukN2FSKQZngMpJHBNxoK4hynyKuV0qttcG47d9Nlsy7LJiuWbCLIPpt2d2G39yQrXQgg8/9sSjFuSbzhmXVb2+zQ7HcraPK7dthftG9WMOSYT5znHxdhRNTxYWDjy8dF4+YJuOLNbMyWB/b2Jq6TKvfC7nPYH0H7Dm22eMyYzUBktrXxf3M9Jznh8yfvTo34sqm0xRjia5ZBRVtbkMPYce0E3aMyXWrAxdofAami3iwDkJAwb42s7jbp+3ruUok/hel4ioFm1QaWPmPtGos9K0E6nKvkX/L62G6xh9xnz9lRF8h6Zc/Vz3MuGxSTm1i/mYG+xtdAqOzaohleSNV+xyhiaaCgnM4c1l9tFOOHFP+PMOYpK3AeGIBwnw8Itn88BoCZMWflKJMqrY5dh7GL5+OpM+qEyyeu7YSr9Mln6EzdhHZCbEz6bttb2My/KILP8ZpUXw44xf2/GoDcnY+FGdVMcwMIJUyL0aomNwBmnYTd8F0ZFkZOiRMlh1qLs6q17cP6wKfhu9nqp30Ll5/Iyn1ibc8pf1Hz+tj3FCUU4C4VJjBYmxvO1vZ7JAnvAVAjhMhp2EfPqRFhMYr6bvQFv/bHSvaADdg+OnSZd1utcZbtYdpIyZzGrrxAL/ZHvF2KzwUxDZutNH2Dt7BQzQZwXQSg0FJ6LzTvZdCbTURkmveS4CFJx8vLoZfjXqxOxdXdR3GdWV7UbyowyptMY6mXxYb5/lUzaV/zfDMxYswNXfDjDvbAF5luRURTZjffmozHJACUT8Kl0BSvTnPtHzMf01dtx6xdzpRxMVa7nRWC3ql5lUWfuG4X7S3HqKxM8a8q9Pms/ztuIZ39Z7JolPhkmMV4dh1lg9xm7LTWVKDEyP2VYNOyAlqjDCtmm3fzZ7Jg4szp2K13ZwcIqI515kFi0cRd+mr9JWmNgXkTUzJW3Kvv8r3UY8l5FhAiZrTe37/Cl0UtdM+8lm/clzVZ0VPpw5ya1VJvDMEqzqxdlSJDj8Iujl2L+hp146qfFCbXFKKo5JVHykgU7kYgwOv/s2q9kyqbjRfCza69TlBiZjKrmc9woKosVDt+dsBKTllcEGJD5WlWu580kJjENu1WUxJX5e1CsGNZYx+ujduOns/HG+BXRKC62UWKSYBLj9Xlhgd1n4lfo8oJ1he2ke1k9VmjqxXV/JivdPMLIfhuTEdnO/u3s+EWAfuqyzYW45P3pOPWVCbj+k1kY8/fmuLJWmBcLI+ZsxKKN8qERl26uWNzIDAz6d2v3Fe/aX4p/WSQ1SSWP/igXf19Hpf/0bltPtTmujJiTWCIPJvyojFBRgV2l/oAG4mWGJD8yDoiAvfbOKKvlVbWP1OFBXvc8B5jHwFfGLLMMVel87dj3MiKpfXNjPzDOxcZznJRGKrKY+bt+fNTfprrkduaFENgj4U/lENzG4QLxh2TNUgH7/mg3v3tojvs5hu9xZb7mMJuoDXsiz7xTrHcnvzipn4+ImhDR00Q0jogKiUgQUX+bsmcQ0Swi2k9Ea4noYSKKU0MSUR4RvU1E+US0h4jGElG3ZNUZFGZh25sDk3sZ3TQjVeGzjNg1wcqMQ2UryM7Orcy0Za02sWqlL3xnGv5YWuGMOmGZdbY+M1ZbvecNk4sUY0ZmYPAiPACQGrzDgsoE5+aEyzBWeBknw2ASM9gQs33yCrnQrioRyawwa9hX2uygxpyjIMDp5BcWodeTo+OOF+5XG7vM330ifvjm785oOmT8yOn7U8t6q5UtLi23DLkolXUTwAMjFqDbo785OhMD3rJ4+23DrmPv+Otct5dnzThvj5q/Eau37rGtRzpDewLqUqfdBaevVna91RHA3QCaA7CN+UREpwAYAWA7gJsi/z8E4EVTuSwAowBcAOBVAHcBaARgPBG1DbrOILEVXiU72bz1BVLdoCREiZPsttms2mbn7GOFbaxcATwxahF6PDFaajIxoj8MZntQo/Buxcr83Rjy3jTLzKJeE+TI2bB72wRbJRF2a+rKYGK7q6IUI1uynIxzHnPg4GUHWuWUoJxO8wvj7daNLP5nV4xGes22PRhhsbNoxmneMMsSMmEevQhRH09dE5MQSOdfr6rtGMbZsBt07KraevM8bReHHdCUIg+MmI/fTRlkvSz0Xhu3HHd9E/89yzjZlwuBT6atRUmZwB1fznUsm+XFht1Kw+4yj7slswLsNexui5RR8zbhkvenx33PL/6+FOcNm4ydFn3KuAhdt30f+g8db+906tFUR4XPpntLeCgrDcwEUF8I0R7Acw7lhgKYDeAkIcQ7QoibATwF4Hoiam8oNwhAbwAXCyEeFUK8DqA/tDHy4STUGRh2cVxlB/QzXpukpGEPRXRHmzGgXAiUlYuYBBFOD+PTP8faaNo90ALAOxNWYevu4rgMdm543ZF45IdF0lp4WWS0UrJRaMzkVnKPIX3B21M91e03VgOsHWHYUWLSDy/aMJWuVrA3sWRIXrn/uwW47uOKxDr9nhtfkbvBhEz0FCBeGNstofH2ElnGTtm7oSDe9McJp8XCFMldCR07k1btf0M5AQz9bQk+nro2bg5Sy9Kqvb4yxjprqMxO6cdTKyL+uO3aJkvD/sCIBRXn25nElJbhr9Xb8dTPf6Nwf8UcIKO9/2NpPtbviO0nL49Zhr9W70C/oeMwx5CrALDeGbeNwy5pqpOKqUhKYBdCFAohHHs+EXUB0AXAW0II47Lwjch1zjUcGwRgI4CRhmvkA/gSwFlEVCmoOoPG3NeiJjEKE4aMtiJqwx4CAcYu65sQwEXvTkOPJ0bjn0gkDqeHcdgfK3DpB9Px5Qxt9Wm3ZWa08VqRv0fROUy+rM5bf6zAny4a+KBR/5lT3y9kybeIfmGHlUaOYYJA5Qm69IP4bJrJYrSk/40Rp3ljx94S/GXYoaqc4y4meHGi88u8zckkRrVV5q/lrT9W4pcFmyJ1xX44c421+YmK2afbQkc1jG0Vl9/Kr50mt3Z/Yggbald0f0kZzhs2BW/9sRJPGZR1srs1RpNZ4251wd4SnPX6pJiy2yzmGLtNAhkNu0CIBXZJukdeY5abQoiNANYbPtfLzhTxo8Z0ADUBtAuwzihEVOD0B0BJvfnWHyuwdntsYh39IVf5cbdJpK4uiUaJka83KOy0uUIAU1Zuw+6iUrz15woA7lrl8UvycVdkC1Y2fKPKokVV07Zrf0nMYOIHf2+Sd1L1+vs6fSVhWOQZkdXOTVq+NS7jL8PI4KXLqzwnVqZyocMoyLrc2nnDpkQFIhmBXReyVm/dgwveniLVHFlzP3eb5tj3usBeXFquNNZqdcVf61p9B8OoYUesJtboEKzkdOpyb98ojnduO6teIgBZff8yCzR9XJcxiZlmMM/08qy6+T1YzRuqtvVGCvaWYJFi3/IDPwX2JpHXTRafbQLQ1FTWrhwMZYOoMzCsBLsKDbs8Mh2mIkpM6oUvu/YabdD1CU1pwJC8NbUBUr4soBbiSVazIpsdFfD++zqdFTJ5Hfd8M1+q3F0eUqYzDIC47fMDkbu+nhf1W5EZAvRdRbsdVCO6Ika7hpz/SKVsOQ2703i1pXC/7ed3fj03zszSK0KYRmIBLDFE8Dn6qbE48cU/sCJ/t6INu/PncxVD9rrFWfeyE2Jtw+5ez67InG9remKQD3IMizfZFuoLs9fGLsORj8c7LxtpVb963DG7W0hGplOv+CmwV428Wu1v7zd8rpe1K2esK4g6owgh8pz+ACQc4FrvFCpCkszDUBKNEuOlVf5i5xw6zzDY6AkigohxqjRAqni3lwul71d2MJSZAKNt8GBSBTj3i3IhoiZKYUDWZlXVtpVhEiGosVXWFOTz6fbZSL2i+63I3FvtqpoVqYqGXeUZlU3iY6cJffvPFej5xBiLhFJavSMVwrX+sTQffZ8da6upLRex35mV2cTSzbtxy+ezFW3Y/e1kbk6ldrLFkn8K8eqYZZY7RVanyMx1BZG67HR0xrYYzZhe+E0tFv9Qm/Lfza7Qqu+1UJLp8djNJCMOu1f8FNj1J9UqI0Ou4XO9rF05Y11B1JlkhOnVHZmHoTREUWJknDR0b32VrWPZW5M1nQHUvq/SciEtKBeXlkvb3kV/X4n5qiL7rVTVFec5tHvxP4U46qkxahUyzAFGULuXx3duJFXunm/ldp68IHNvuqZRRhOuC185klpzQH7hYjcdPmmTSIoImL5KLUrUJe9Px7rt9iJCaXm51He2eVeRUr9RmbtkcPv67aLmnPTSn3j+96V4aOSCuM+s5jW3KDEAoubBdt+HsV6936zbvhfvT1rlWrcMt34xF5OWa4EiVCK5FSUhSoxX/BTYddOTJhafNYHmEGosa1cOhrJB1BkIdppbvU+qWILImI1URIlJvcQus4WkDxR7FR4c2VtTtRmU1bKXCyG9alBZiKis4PXvwCnRgtN5VpyuGDaNYQ40ysoFFm8qdC/ogTCYMcqMrRUOjwoCu4IjqawNu5c57vy35OzoAeCTaWvc21AuN8/kFxYpJ07yU8uuh1i2q9PNh+yXBf/EHbM6QybC2dsRvzW77+PyDytcE/XoNbv2q0QMcy/zn0geAxUz1ANFwz4n8nqk8SARNYUWv32OqewRRHExhnoB2A1geYB1BoJdfPFopkqFQdoqBJFdmdQP/XLxxKMLDIXRTPY7k1ntV9QJ7JX0vC8rl//VBOTNZ/TFi8zUpvcf1WQir40NtLszTMZSu2olPDhygZTzvxdCoGORGtd0p1OZSIC6wF5JwdxPVrhX/b5UYs/MXVeA+7+L1yqbKS0vlxasrcwv7NBDH/uFbhJj11S3xY/Vx16dTo9p18CxLUbc2m2Fyu7EPo+5UsKGbwK7EGIhgMUAriYio6vydQDKAXxjOPY1NCfQM/UDRFQfwHkARgohSoKqMyjshOyoQYzPNuy6Fj4MGnaZFMO6zZ+XGLWudZeqOPkIqbjCQMQkRlbLXy6/wFByZI1U+fzv8nZ9izbuwqj5Vv7X4aRfhwapbgLDROnVui4+nSZvP26O+ezEH0vzQ6FkkRnYdIG9Zd1qrmXfmbASgJpJjKwNu5Vg5qQkUhlfZZ2RyxTmApXEO0L4G+lN11TbyQVu17Kaw6yqklG86T4QMstDvd0qixel+BUhkJP8IEe2IBE9EPm3c+R1CBEdA6BACPFa5NidAL4H8CsRfQHgEAA3QoujbpQ4vgYwFcBwIhoKYCuA66EtIB4xXTqIOn3HzmTBS5QYGfOHaL8OQT+U0bCXeIhqI1tSJZudEEKqvUDE6VSyFeUiqAFd/QfeHpBmMCjq17ByPWGY1KAqQJljPjtxyfvTFVsjj4qwI1NyU8QxvWauu5gwLWIzrhKqUVa4NwufxaXlGPj8H7blVbIc51aSa69KdBWZHXKdMiE/x8igL4LsmusmaFt97CVxElCx0JL56rKynBcaVsiUrVe9snQb0gEVDftjkb/BkfeXR97foRcQQvwI4BwA9QC8Gvn/cQA3GyuKJEE6FVpSo5uhZU/NBzBACLHcVNb3OoPATgiLmsQoOju6oT94YdCwy9izRYXqAJqrIrCbvf2dKFMQwlXMZ/SJNd56K54Q/LyBMmn5VltvfYZJBfFRR9IDlZC5MuPKS6OXSZfVqaTgSCqrYRem25q5ZoejZnzNtr22n5mpkuOeERpQ07CrzUdqkcjc0KcUew27m8Aup2GXUiqW67KPvIZdRZ4Rwr3uUw/VXBjD4DfiB9IadiGE1NMlhBgBYIREuR0Aroz8Jb1Ov7GNlKJr2E0d65RDGuNnCwcPQE5T4mUhEBQytmRebO5ltctqJiZqgrW0DbvE4BEtK1knUPE7t6pXDasVJqJ04bIUZohkGCtUTFzChIziRCeInU4g8VCNMmWruGjF61WvLOV/IIRQ0rDLtll1x9dPJizbir837UKrevFxxwEJkxhJDXuxRF/T5RiZO9T7jUpsBZnFTpjkJD/w0+n0gMZOw15YVIrrP5kZ12kHdGpoW5fMA18WIg27TBuiJjEqNuyS5YwJLFzrVBCsNa2KZFmFhYCXxBpusZD3Fpfi0g+m4/Vxy6WcxMKCinkQwzD2qCR8UZo2FArLOp2qaJbN80uui1ZcJm48oCmRZNt7zzfzpGPMq/oo+T2F//utKbZzspcFgtUZMjKK3gYVkxiVaGjlwn0RVRH0IzOQ1rAzzjjFIv9pvrUm3Q4pkxgPtvFBIbMT6ykMpWTRDyatlq5SVcOuVK/HCcgJ2da+O2EVxi/Jx/gl+fjkyl7S9TMMkxnI+uYAwc0b0mYuQr4N5mHYTSCX1VfsLS6VbsOEZVsxYdlWqbIqSogyBT8pWXbtL7Xd9fai4LMS8mUWJaUKJjF6xKDP/lon3a5y4b4YiGr5wyAo+QBr2H1CZbAE4DhaqZnEpL4nymVm1Z1O5QnC7kyo2LArZkWVba7SmiVS1q0pRrvbNFKwMwzjEyqhX4PY6VRBU3BImhAqznGypQv3lwYyfz77yxLpsn7bsOuY7f51FKymKuqyOEdmUaIyf+rx43+YK58uR0bDHnWdC4Gc5AesYfcJle1INzLRhr04ahKj5lTiN9r3Jm/mkiXnuqFtbUpHlNE0FHomOCee+3UJ3pmwEgV7naOSku0bhmEOBN4YJx9bQWasat+whlY2AOFexRREnw7nrCvAR1PW4LSujeUb5EKqp0+VnQYVvDqdWp8Tf0xKRlHQbiuE74+r37FMiOQkP2CB3ScSyY51QY8W+NywFSTzMKg4dASNzIOjqmEPakWsGg8/J0vF3l22DQIXvTtNus+4CeuAXMQZhmEylxFzFJJ5S4xV9WpUjhSVHzTlkyGphcwFKsJnukWVkh0Jg9Juq6Cy06BarxVeruXVT64irKP7+RUx2+XRTGJkbdjDICklDpvE+MAXf63F87/Jb4OZ6dm6bsx7GYG9wlQi9R1RKUqMZHuDcMbR6lUM1ahgly6/GFGLFcwwDOOGTIIjHZmxyov9r66Vd0NNwx6UUAukWuWlEolMBT2GvhmVZEM6XttXXi6QX1iEySu2uZZVyZCrI4RgG3ZGjT1Fpbj7m/mYu36n0nnGxzTLpB2VEYArosQoXTYQlHYEVITlRBplg4KpeYBhHf2/M2MXGvzONN/rZxgmnDSqpSUeO++I5tLnyIxVXkLxVpGM0CJUnPTLgRcjMeH9JAwadhWfKhV+W7TZ8rhfTqcylEV2kmXQ23WcQ/S8+HPkNexhkJP8gAV2Cdbv2IszX5+Ej6auiTm+fU8xBr8z1VOdedUqR/+vUSXWMqlMwjNE74h7i+QdjYLCixOlG0FpVVQmiqDCOgYxeBAbrjPMAYn+7OcrJHySGdZUnAZVUVGcFOwrxitj5AV2FbPLVMtx5UEZsfsaJcZbE0rLhXTIZV3zX72KvJW2zIKrwnQ41b+0P7ANuwR3fzMPc9cVYO66Agw56qDo8es+nqmsWdc5qnU9DDnqINTMzcFB9WK3MuXCOgr8tXo77vl2vqfr+4nfKbEBNRMTFfYWl6GGRKptQFUIV7Fhl6xUgZ/mb/K/UoZhQk+5EJi8fCuGT1njXhhAwd5iqXEtyNwZKgqZjZLxz411yxCUdlsFlWAFfl1P/Rxv7ZPxbdNRsXc3nuPWh6LBbDJDXmcNuwwbC6ztwaatSsAOmYDHzjoEd53cKS7Rzb4S9xCR5QJ45PuF3q/vIzImPDpqSYu8tsiei9+fjl9sMsyaKVexYS8X+Hiq3IQZhN/BP7us+yjDMJlNuQAe/XGRdPmSMrmsnUFqJ9XyYajVLVu+XMGMMSiCmufs5uSxi7dg6K9q/nZe26eatVS7mPw5MjbsmZY4iQV2CYIQsLISjMNXVi4SikzjJyoradmiQToEvSRpD6ntdMg7yb4suW2bKYMHwzCpp1wI6eyeOjJTWnSnNwCTR4Xounhp9FL5BkB+vg5qF1eFoMxynBI5vjZuOVZv3WP7+cg5G2Lee9awewjhrHJOebl7+TBlhPcDFtglCOLHNobhk4yEFYMQIjQp6GVMeABdsFcpm1pUNOwqZkFfKmRzYxiGcUJ1fpIVEUvLg0t2Vy6E1E4yACzbsluhBfJjcRicToPS8udWynb8fLeD79stn8/xpQ2qmcKNr7LnuBXnOOwHIF5CIblhlLW9xNAuF+nnaFhcVi794CzcuAvXfjwr2Aa5oGLDrjLozt/gze+BYRjGjBflhsx4VaoYije/UN7p9einxkqXVUX2+1CJ7BUUQWn5X3NJomWOTOdEonHY5a6hvapcSmaxE6Z8NX7AArsEdp2iWV5VbFB0iNExPi9exO4gPfiDorisXPrBuei91IcmLFXRsGfKEp5hmLRi1/5SzFMOK+yOHtZx9Tb3jMwA0OOJ0UptCAolp9OA2+JGqrT8MvL6rv0lSrvMZmSi3el4Cb+oFoc91b+0P7BJjATGTnHii39gbWQAO+KgOp7rNK5wvZi2lIfIJEaWRB7+VKCWjS/gxjAMw/jAnqIyyYgyAss2F+J3m5jeYUVWeXLtxzOxXNHcxm9+mLsRN3yS/J1kN9lhf0kZuv3vN3R79HcU7HPPtG2Fl2AUKoK1bBz2nXtL8OO8zIiixgK7BKUGm5ilm3fjnm/nAfBvde7FtCUdnSjKBbC3OPVx42UpL7fPGBdfNv1+D4ZhDjwGPj9eqtzOfSV45IdwRCJTQdaEdUPBPjyc4khro//ekpKs124yx/Itu6NKqKkr3TOVWqEUjCLym6nMojImq+UCeHDkAoVaww0L7BKUmLZ2tkRs9RIRmmNMYjxp2D1fOmUU7C3GnV/PS3UzpFm/Yy8u++AvqbJ2meUYhmHChOzcUVImMGm5N2EtlbB5ojtuJrXP/LI4+r9XZZSqA6nqOUII17aVlQv8ulAujHM6wAK7BKWmgKLRbbQExoVEHUaXb9mt5DgSBr6csT7VTVDikR/kYxt/Nn1tgC1hGIZhZEhH/65k4/YdTVi2Nfq/169T5Ty9rNo5clFiVEOehhl2OpXArGHXSUTDnpWghh1wDs0URvZLhvFiGIZhGCYYShVC33mNY7Nyq7x/gBcb9u17SlxlMFVn7LCTOUuPACmx6dyJ7LxRjNOpN4k93TQJU1ak3/YqwzAMw2QSKrLDgg27PF1D5Twv8dIf+3FRyqP8JBsW2CWw60QJ2bDb/K/CLo/e26liyebCVDeBYRiGYQ5owqbsqzCJUWtXOgbfSAQW2BMgka6SqNMpAOlMcQzDMAzDMECswB6GCGd/LM0HoG61EIa2JxMW2D3Qt319AIkF448xifGoY08zn1OGYRiGYVJMqUHQDVNUHVWN+Qkv/hlQS8IJC+we6NCoJoDEbNiNeBW87ZxhGYZhGIZhrDAK6WExjyktK0+rxIqpwHeBnYjaE9EXRLSeiPYQ0SIiuoeIqpjK9SaiiUS0l4j+IaKXiaiaRX1ViOgZItpIRPuIaCoRDbS5tlSdKlhFYtE7uF/2U6woZxiGYRgmGZQZlH1hsQM//dWJodL2hxFfwzoSUTMA0wHsBPAagO0A+gJ4CsDBAIZEynUDMAbAQgC3AWgO4A4AbQD8y1TthwDOBfASgOUALgXwMxH1E0JMMVxbpU5prBafusDuW9cKmcReOTsLxWXyYZ8YhmEYhkkPjCYxK/P3pLAlFSz+pxD1qldOdTNCjd9x2C8CkAfgGCGEnvP3bSKqCuACIrpcCFEC4EkA2wD0F0LsBgAiWg3gHSI6TggxNnKsJ4ALANwqhHgpcmw4gAUAngFwrOHaUnX6wepte/DNzPW+xRVPNImS37BtPMMwDMNkJlsK9wMAZqzejkHDpriUTh7b9hSnugmhxm+TmFqRV3Oe9n8AlAAoI6JaAE4AMFwXrCMMB7AbwPmGY4Mi572rHxBC7AfwHoBjiKgJACjWmTATlm3F7V/NxdSV232pL5kC8mldm7iWSbcMqgzDBMuwiw5PdRMYhvGJh0Zq+tT3Jq5KcUsYFfwW2P+IvL5HRIcRUQsi+g80M5ZnhBDlAA6FptmfYTxRCFEMYA6A7obD3QEsNgnhgGZ2QwC6Rd6r1BmFiAqc/gDUlr3xREimeFynWiXXMlksrzMMY6BLk6QMhXHUruo+XjEM441NO/enugmMAr4K7EKI3wA8CE3bPQfAWgAfQxPW/xcppqt4N1lUsQlAU8P7Jg7lYCirUmfo8Jrp1AvZEtdiDTvDMDodGtVAg5pV3AsGwKibj0nJdRnmQGDJP/4lMxzYqaFvdTHW+G3DDgCrAIwH8B00m/LTAPyPiPKFEMMAVI2UK7I4d7/hc0T+tysHQ1mVOqMIIfIs7yBCsrTsMkK0X9gtDrq1yMOcdQWRMklrDsMwIaZ65WyMurlvyiJJsPKAYYKhtKycky+mGb5q2InoAgBvAbhSCPGOEOJbIcQVAP4PwFAiqgNgX6S4lcom1/A5Iv/blYOhrEqdoSMnO3mTkt0EeFa3ik2ILLaJYRgGQP+ODVEpO3XpOrItxqKbj2uXgpYwTGYx9LelqW4Co4jfI/H1AGYKITaajn8PoDqAw1BhtmLl/dgEgPHcTQ7lYCirUmfoSKbALjP3srjOMAcO1StnWx6/sGdLPH7WIQBSp+kmAIc1N21ystadYRJm2B8rfK2PI6gHj98CeyMAVqO/7jmUAy0kYymAI40FiKgyNCfSOYbDcwB0IqIapvp6RV7nRl5V6gwdlbKSp8Gym3iFRBmGYTIPu+f9qXMORZ1IXORK2Vk4+eDGyWwWAG1c+vb6PrimX5voMR6dGCY1HHFQnVQ3Iel8fEUv90JJwm9JcSmAI4moren4hQDKAMwTQuwEMBrAEJMgPgRADQBfGY59DU3Yv1I/EMmYehmASbomX7HO0JGVRXjlQstANr4j4+CaTCdYhmHSg2FDjkDHRjWTek2CZhZzfb92uPX4Dvj1v8e6ngMAnZvUci/EMIwSIgW+LA1rVsFhLfKSfl2dqjY7kKnAb4H9OWha9ElE9AARXU9EPwE4C8A7QogtkXL3A2gAYDwRXUtEj0PLjPqzEGK0XpkQYho0YftZInqGiK4GMBbAQQDuNl1bqs6wcsZhTXHJ0QclXI+bfaeUSQzL6wzDWCAS2PiuWikbn17ZSyniTF41TcNfu1ol3HJ8e3RsLLdgOLZ9fU9tZBjGnllrC5J+TQHgg0t7YMhRictHXki2S5/T5fwO6/gngN4AZgG4AcBLANoCuBfAjYZyswAcDy2qy4sArgLwDoDzLKq9GMDLkddXoGncTxVCTDJdW6XOlNKhkdnCR8MPzXbfDg0cP7fLqmpcOCczag3DMClG4XEvT0DBlpNN6N2uPj64tIdU+e9v7IPKOfFTlIyWr0HNKqhicS7DMOmFEEDd6pUxxAeFphf8tDh4LOIT5BXfRzQhxHQhxKlCiCZCiMpCiI5CiKeFEGWmchOFEH2EEFWFEI2EEDcLIfZY1LdfCHFnpL5cIURPO425bJ2ppFuLPIy4oU9g9Ze7zKgyq0Wn/tlJUsPFMEzi1K1eGTWq5FhGS/HCfad2Suj8RLbE2zW0VlTY0bV5nuVxt0XDSQc3wr97tMDYO/qjT7t6lmW8xoyOc4BlGCZQ9DEnVWpEv657WtcmaNugekJ1sAoiyTSvUxXVKgcR/l6jkotWKdGQjVUqhceei2EymXO6N8OsB0/A/EdOxIonT/WlzquPbYvvb/SuMPAqrvdqXRcv/1vz00lUYeVkltO8TlW8NeRI1MythGZ5VW0dZQf3aunp2pVzsmIcYBnmQMFtxyoo+3a91lT51vmhLKlXvTJeH3x4wvWwwJ5knLp0WSL7zQDeHnIEqhoE6pcv6BZXRiZKDBvEMExqqZRNuH6A5o+iMlEd3LSWq0DZtXkeerTSoj20qGuZU84W1Tm5ca1cfHBpD3xxzdFoWa+a2sk29OtgrR0/u3szfHNd75hjds01DrX9OzZAzSrySpR7Tu6Er649Wro8w2QCuS7KuqZ5amOJLPpCIFXpYWrlVnIvZEE1g7OqPoTbmSTLwgJ7iEg0m+CJJm1SZQsPU5nVopOAcF0/cwAghmH8Zsb9JyibkADAqJv74t5TOlt+1qhWhbPnnSd1wmldm+CDS3tYmtHZaaBVxqibjmuHKfcehwE+pyzv2bquZai1S3u3QqNauRZnxFMuBIZddARuHNAO713SAxPvOQ7X9Xcf26rkZIOIUKeat0mcYTKRAR0b4M6TOgZSd62q2rOWKg17tSrZeORfXWw/72vj4H7Tce19bwsL7MnGYb5LUMEOwH27WabPO21tnXxI40Bt8J3o3jIvJddlGBkedhjUAaCVgoa5ts8CYZPaufjp5r7R9z1b18Xrgw9Hu4Y148adw1vm4cmzD7Wsp3V9eRvM20/saDnJ6pFfAOCb647G51cfJV2nzjEWk6TK8CmENpbdcVJHZGcRalethKPbWNu761SvnJ2w05gbpx6a/Fj3DCODk1zwwWU9Y55rK844rKnj51Y0rZ2LN/6jmZKkSsNeVi5waZ/WqGST4LJX67qWx42me/pXl+iagwX2ECFjA/bBZXIRFuywNYkxXDvbJfNqtxTFRD24KcdWDhuNJTWaBwKX9WmN8Xf0t/386mNTtzs1sHND1KthHU6xzDTuWEVm0Xn6nK7oZ4hEpSLA6zTLq4rbTuiAO07sgCMOqouj2tTD2d2bKddjRm2HMr6s02R6y8D2mPXQCYb79V96+PGmY/DcoMN8r5dhwkCnJuoBKybfOxAHN9UcvYNO6PgviwVF2wbV0cBm3NSpZBMr22rnMtE7YIE9yTg5TMlMOCo/uFVtdqvUFnUrtH92HZBhzLSoWxUNFeJqZzqtHATYcw5vhifOdtfQDrtIzTnpPxIOlP/pZR8S7cXzu8W8d7KzbFw7F/93eU/pttlx88D2uNGwZXycD2YzVhmj7exPVWT7e0/phFtP6IAqOd4c7t12XgDNfPGQZrXTIst0k9q8SJfByiQ1nUnUACAFOZeUGNAxNiR2dhbh51uOjQbqaFPf2kRxYOdGloqLUw9tEv0/asOe4POdWT0qzZExiUl0QLc6/7I+rXBil0ZR+/YLe3iLoBA0iTpsMP7SvE5VPDvoMHx17dEYdETzVDcnMA7yyVkyt1K2o+AMAA+c1hknH9LEsYyZ6we0Q9PaubaJ1ybePcAx8+dpXZtg2n0Dla6pk5NFeHZQV0/nGjm9a5Po1rcXurfMQxeLHbjTuzbB8Z3jFwNOuwhmrPx+VLT5Azq6L0Z0RU4ayOsJ7/KmkmTG5m9vk28lk3ngNGv/GT9INMKdG2cc1hTPnFthClitUnbMOPHmRYejq0VY11q5ORh7e7+YY7/+91i0aVDx+zuZxKx88lTHnVkjLLAnGadxXkrD7maj7kGoffhfB4OIMOGuARh20eG4rE+ruDK929bDb7fKpQVnDgwm3n0cWtevjoPqVcfNATjYpJLTulYIzce2t09G5nfKbC8amGZ5VTHpnuPwvzMrtPfGaprXcV9wyDprmqlaORvnH9kC71x8pKfzdYgoRiOlyrfX9bYUrHOys/DuJbECZpv61a1t4G2GX6vfRCWil4ySRbf/DbuG/YYBbdHOIIioRhlKNclU8ob8p1RH4su7sm8bfHpVvEM4kHjYx6C/zpzsLPzboKw0t7ZNgxr4/sZj4s7LyiIQET64rAdq5ubgqXMOjcvIrPskWd1DVhY57szGlJUqxfiGU5+V6c+JDuhOAkHTvKo4+ZAmyLHYyrvthA7o0IiTJjHWpNvk5OYAdbFkGuznBnVFz9Z1lc1Y7FD9Gu85RUuEZH6uv7j6aDSvUxUvnK9uE+2WywEALj76IFSrnI1nztW062ZZOaiIEXaoLHR+v62fZ/MWHTsHNCuczCABoHbVStEFT6oc62S586ROMXPQv7qqOxKmlCSbZXx0RU8c1SbeKdGPBISfXmktGKeaHAvTND8I62JWzww/oGNDzH3oRFzYs0Lov2Vg+5gY7Inm4GGBPckEbcOeZ4guUb9GlbgtHIV5JoYwmJ8lGvaSCY6gtytlkLEP17Ha2jRi7Gmnd7XX/HZoVBNfXnO0khnLqJuPwZ0ndcQQi0WB05x05EF1Yt5f378trrUJs9qzdV1MvPs4nHO4uqlSD9N1rHj0zEMw56ETo6Y2fds3wGHNa+O4Tg2x8H8n4YZIDPkwYhfaVkUeaNugBk6T3BFwG7ZmP3hC1JE/CKEkR+HZrF3VPTqRsYluI3KiOy9+0MDgY3NJ7+Smt+/bvgE+v/po/HX/8b7XXbVycpMYys6+dl040enbr2zPfmN8Zs3z4K0ndMCMB46PjpOdm9SMs5XX0R3vnX5XFthDhMw2q5smqVGtXDzyry64pl8b9GhVB19f2zsmprJb8oMwc5JN1sKw8uiZB6e6CZ443EP4zDCMpdUVtBduiz8hgD/u7I8vrzkavVzC/alycNPauGFAO8sQgU5f47AhR+D2Ezr42hYj/3d5T9w4oB2ukcy1YLTvrJyThZE3HoP3L+2B6gpJiBLhvlM7gcg6QZwXVAQKIsLr/zlcShiumev8fRgneb/l9ZsHypmqVa+cjQ8ulbNNN85B9arbh/Jr26A6+nVooJQZ9uSDG+Piow/C3IdPlD7HjaPa1MP0+wfitcHdcUeSd350GtSsgq+vPRqHtcjDR1ck7rQNJF/jLHs1u3ICwE839/U8V9SvURn9bYTdILAz4fnzzgFo06DChMVtQ8H4vGimMz0x+rZ+OLpNPbw15IjoZ8+fdxim3Huc45jCAntAeAl9KDNhyDyjl/ZpjXtP6QwiQuWcLNxxYkfUqVYJPVvXtTR38attQfLJlb1sExSEkQl3DcDFR7dKdTM8IeOQZ06sE4btyhyv20cWCCFwUL3q6GkTYzconBbk9WtUwVXHtjGU9ffa/To0wB0ndVRyyEwlVx/bFvMfOQlndks8JCQQH95Sx8n2VmZYrJyThTEmpzQ7rH5/q50YGd6/9Ej8d2D7aOIZJ8bd0R8DOjVEDcnF1n+Pb4+BnRriIoe2/X5rP1TOycK9p3TGiidPxfPnOZtnPXR6FwwbcgQePfMQKU2/Cg1r5uL0rk0TNoVSwexPdmSruhh5Qx/0bd/Al/lURePsSyhmm8u9emH3mPdOt9alaS1c2Vd+ARdzeSJ8eFlPHCGxA3hil0ZSdTZzyM7awCb6Wct61WKUh140/+0a1sBnVx8VU09WFqFJbWefkPQYmdOQDy7tgT/u7B83AKo4nTasWQVjbu8XE4HDi2BUt3plTLl3ID6/Sj1BiY5ZS/TzLX09aWK90qdd/ZRlOvNC8zrp5YylwqW9W+EJk3bY7pdpmqQQcK3qVcPxneUGaRlStT5VSXzG4VchLWDKYBU32Q27XdGWhjC5WURo26AGulhE6rnpOHfTodtP7IDDXEy4rOjYuBaysgjPnNtVWqv55kWHo66D1lznv8d3wHuX9nDcsTXuHGRnEc5NUSSpGwao5z947xJ3U55BRzTH6qdPw5LHT8ZJB8ePPU7mr25+DZ9ddZRruNwYUwyX3/fB091Di3rh2UFd4+KX28k4qsmD3rSJGuW2O9q/YwO8fEF3y8+6NKkV9R84vnMjDL+iJ/q2rx+zu/Tk2YeiXcMaGGbQfpsxNiGZyioe8QOCCDioXvU4b2GnrmbuiG0b1EDbBjWijmWVsgkdPIaKyq2Ujaws8uSpfdNx7eLCwnVuUst2u/WVC60fFjPT7x+Y1C0uWdy2sGXQFxdOKY3DShYRTjnE3vyoWuXsuMWT3WKqZ+u6GH3bsegYsMPymNv7K5l7uTlGmQdhFbMLuyyhMriFnTPGGpe1oWbk8FP7OuKGPmhSOxfHdWoYNREyj+9nHNYUt58Yb6JhNpnIq1YZIy2iU8hyQpdGmCNpYtK1eR5mPuC/vbUMpwSQ5XXWgyegU2P1hHtuO2vX9msbFYKr5GTjrSFHopYP8wagLUKPblvPNdSqcYga6rJ7UbuqD3Ma5GLL28kY+iJFRsC9sGdLnGIzvrktrD+8rKftoqBcCHxyZS88O6grXvj3YWjboAY+uqIXBhjyQAzu1RKjb+vn2G+M98gCewagCzAqjpJ2/bB+jSqYcNcA/H5rP9tEILLIhg8yYjWpAPZCmuyioGHNXHx4mT/2fGactrqSyaV9WmPCXQNS3QwlDqpXDS9d0E0pwoidhicnOwvtGtbEFce09ql11jhtS1p10zrVK+ExGx+DQ5vVjtt2PbNbsziNj10klMG9WuKX//aNOWbnfGfcdm3boDrOOMzZvCMrizD9voH4/dZj0Z6jNvlK77b1LBM49Wpt78Nwqo2QWbd6ZUy+5zi8b9DcmecCu7mhb/sGlpFFVDF2e7d5I9fg6JaKnczp9w90NQewYvFjJzsm3ZLZLbCiZm4lx4XLPad0cjXbcQqxbDdFHnFQHXx+tbYTTkS4/1S5uOZCaM7sVvbPT5x9CBp7+G6t+OKao1DfJfOn3eyv37Oe6K1l3Wr4+Za+dqVt6y+V2AlzEqLr1aiC849skZAsVdsQ3EMlYlSisMAeEHp/Mfct57COsR8atekt6lZDq/rVE7Zb7dGqLh476xD0bKVNCPed2slzXTJZU/3m6XPktJfnHO6PXasftKhbDVf1DVZg9Yuj29TDPSd3RpWc7GhKaDNWk4LdANlCjwGu0G+/ue5o+cIALu/j/N1mm9rWv2MD/KtrUww5uhUet3D8/P7GPpZ23Manc9hFR+D6/vZb7Z0a18JNx7XDLQPbY/XTp+EEG5vKb6/rjZuPa4fJ9xyH0bf1k4r80LBWbsYK67qZnYypiN9kZVGMgA1oduCHOpijPHV2V9xxorUjsFnwjZsLHNois1v0rksEFlmfjucGdU1YEZQoDWt6M53LrZQd95t55cebtF2MxpGcBPVcBFMzKnvXdqZU31zXG4c0q+hvVx3bRmoXWkBzZj+/R4u4z/7T6yBfggIQEbq3rIMRN/SOvbAJu4WofrR5nWqY/eAJ+P22Y213FJ3kJKfgHHryNbv79csXb8hRB+GoNnVxy8D2SV3gJsed/wAmXtvsFNax4v+auTkYbJEV0Y/OMeSogzDkqIOwa39JQgO1lQbhgdM64/CW7k4hXrmgZ0uUlgs8MGKBbZmbB7bH9f3bomGtXDz/2xK8MfhwDH53mlT9nRrXxIaCfX41N8r9p3XBwo27MHnFNsvPc7JISnNg5Pr+bfHG+BV+NC/KZ1dX+DmUlpdblsm2MCexEthPOaRxNEKESq89pFltHFSvGtZs24s61Sphx94S27LDL++J3m2do7gIAO0b1sCyLbvRql61mF0d8/P54OldbJ+xotKy6P8dG9d0fRbtdqaMtKhbDbdJlDtQGH5FL8xbV5B0Z187juvk7BdRu1ol3DCgHYb+tjR6zC6rrLmv6UoTK+47tTPmrd+J8xzsvqtVsRfqLzqqpZQQXCs3B+cdGS/kqfDk2Yfivu/mJ1SHDP86rCl+mLsxsPoPaVYb0+4b6N3hVWH4VnGQtxJQuzSphY6NauLgprWwbXdxdKfHTiD1w2xDr8I47lna4tu04axuFbbudSI7H27aeCvM82SPVnXw1bW9sXNvSVTzbXe/br4DstTMrYTPr1ZTLPkBC+wBY15tyjqdznnoxMDjjiaqVbFqnhcP8BsGtMU7f65CcZm1gGjm3MOb4+Opa7D4n0LLz2+LhL4bctRBuKhXS+lFzg0D2mLIUa1wwgt/yDVcEbvfvn/HBvjfGQdjyoptuOdb+YlPtn80y6vqaRFiI69b7l5YDYRvXlThtCP7G5x8cGNUycnGmNv6ITuSQa7VPaMsy944oB2O7eCufaqUTRh+RU98NWM9zjsyVgAyjv0/3nRMjHbLTF9DxtOwmFxlGjWq5KB3u9RGg3ptcHfc8vkcaXMEIsKY2/shv7AItatWwkH1rHcYjX3tthM6OEZY6dCoJmbcf7xjfgPzzpFOs7yqePwsuZ1IP8SXwb1aolzEKlHsnGSvPKY13p24Sqre7CyKEVbPCFhgB7xn/AXiBUmnIe+F87vhwnemonB/afSYXTSgEot58fsb+yAri/D9jcegrFxEdwTtzFH9VAK7VWXVgsn3HIemFmOmnT36yQ4+VPuKy2Le63OL0UzF7n5PUciXEUbYJCZgzM+as9Npxf9hTRIQg0QTZUIx3nlSJyx+7GSseupUqctWrZztYPsWi5uguPLJU3HNsW3w7LldcedJndC4dq7UJNapcU18d31vtG0g7xNgFzbuibMPxUH1quPfPVpEt2VlGCQZdUE2q57ZoblJXvzkNf3+gZYmT26bAzJaq8Nb5uHNSMbQnOwsx9+ubYPq0jGVnz6nK5rUroqbB7aPs5M1LpKbuES0qV+jCqbfNxBzHzoxbUIfMhp68isZR93TuzbFgkdOwuUKfhdtG9TAUW3qoXOTWrbZDI197eaB7V3HeLOwblwIdGuRJxXezhWfTASMguJ5RzTHOzZRVu4/rbNreEedX//bF8cYFm9O/o7DL++J+jVi7dWTHQbYbkfSikOa1cachyocgRvXyrXMywBUJNTRObFLo2h45uwsihmLikut2+BkTy+LXoPRL+AoixwVVjsCVsI6YD0nfnRFT6VgFFYLV6u54+lzDsX1HiIGhQmedQJC35IxDmS5lbJw/2n2WhsvYcWCQh/8bk7QllTWZiwrok2VxS+7sawswr2ndra0/TNjFGg/uKwHuresozTf2f2+WYatRicNr079GppD20H15BYL5rBbVnRvmYf3Lom1Ba1fo0rUAUrHbpvdbX3Zr0MDHO2SgMhNSDdit5PT2uRU/f2NfXBWd3t/htKyit9EJkdBw1q5MZocJj0Yet5h+PCyHnhe0pE6iCyS5r6pysdX9MKDp3fB/EdOxHfX90ZOdhYuPjpeK6sSCaxhLTU7bTuMV/zvCR1sxwkiQnUHUx4j7RrWxK2GRGFOY8OxHRpgxA19ou/POKxp3HimY+UobBfhJbdS/Jgw8W7rIAJuvjRmZJVy5x3RAu9efCQ+vqIX7jypI54bZN+H7TIb+6n/y62UjT/vHICfb+lrOQfZLRqssBLu+7Zv4Phbv3xBN1Q1+HjYBfxqY3reLujZMqlx+IOABfYAuKBHi2h8YKNWZdaDJ6BtA/uwjCordDN+a+R/vuVYPHh6F1zmMAjJNNfOg7qRwkTx3KCu0mX9wG7C++nmvji2QwMMOqJ5haZWQWK3E8bN2g+n+PbndG+GUTf3tdVYWHFa1yZ4ysVZ94zDmlpqzo9qU09qsM+rVhkX9rRf9FTOycJnVx9lm4wCgPR3+dlVR+HfNna3P93cNyZphltUJONzYzU5M5lBbqVs9O/YMKWZnh88vQsObVZb2nHeTIu61XDFMa1RM7dSVKB59MxDHJ2fjfx8S1/UMSw261WvjGEX2ceaNlIlJwufOeTxMA6ZdqY6VmXdMAp01Vx+O6PdcpemtWx3wZ4bdFhMxKf6NSpjtE1iq0+vOipGUXNCl0ZoXsfa5Om2EztEnR5VcZq/s7IIx3dphGPa18cNA9o5Kgz6tKuH767vHXc8Jzsr4cAHRiG6Zb1qtr4aXVvI5wzwIvIc2apuTCbcVjaKq5//29cy90E6wzOUj8x/5ESsfvo0PH1uhYBpXEDabZXqJLL681tgb1CzCq44pnXUOcQKOxMPQLPHq1OtEh7+18FxmtUmtXPx8RW9pNrx2FmHJOwUBSAmlbBXcrKzMPzynjExb0sURpzbT+xgqREz/3QfX9nLNlzcZX1aK9tZVsrOwoU9W2LWgyfY2kk6mXjIbvw8dU5XV9vuTx3uzc4h6NOrYvvK0W3r2dr2Vq2cHaPJdHsq/t2jBdo3rIEzDktuFkTmwKNtgxr44aZjcEHPlu6FFZCNPtO5SS38u0fFtX91CA36w43HxGgx5z58Io52cO6OiUvtIlUY29umQXVHM8DuLfPQsVFNdGlSK8YEqG71yhh/R/+YssZ1gtN0WL1KTkyM7xO6NLLdETi8ZR38dmuFMO+0GKmSk41TDfWqzMh+zd96JBddUWaMTnX/aV1iTIyU65Ys17BmrnRm36YWZpcyVM7JwrODuuLkgxvjrpOsI91Vycn2PWNuqmGB3SeuObYNalo4caqYuVwdSTsu40hnxirUXtA4xZh/7KxDMOOBE9CqfnW8f2kP/O+MipjXD57exXai0LXYOqq3ZZdh9INLe1hmo0sUpx0TMzVzK+HRM+PtFM3bf9Uq56Bl3cQXGGbqVq9s68zjZq4ii5vjcPtGNfHUOdY7JnbdqXfb+lJmPVa4RUeoXiUHv916rHSyL4YJG+Zx2Cnkp1GwdpozDm1eG9f2q9DcuyXMMbbATcNutMX/1hTG0Eyl7Cz8fEtfLca4oQ2Pn3VI3O5ZbOZP+YlDpWzvdv6Mk2b8Vrj98t9jcW2/tnjMNN+o5IWpnJ0VY1ai4hMgOy/Wq1EFX1/rLdrK+Ue2wLAhRzjuOKjcbzrAArsPDDnqINxrE1FANvIJAPRpVx8T7hqAdy6W26Y04jZIBoHbYkQfhKpWzo7RjjgNTl2a1sIz51ZsGas4yxzeMs9WW3NQvep4/vxuUvVY7RzYZZJ7+pyucTG2D2uRJ3UdJ+y0zUH8zCNv6IM2DgPs4Eiii6YuTpmAtnAFYlOzm7ETFJwiYnjJ0AvITcapSBTDMH5hNBs5rHltDD3P3oQwRrB2ERIH92qJZnlVMeiI5o7PJhDr/+HmkH1Is9p4blBXvHfJkcir5p7YyOjf9NlVR+Hxsw6xzMRsfIxVFFjnSjjvv3vxkbjymNY4X2G3t5KET4yO31mL9QzpjU1jtsowuujRkzD2jv4YcUMfXNe/Lf53hrVTbKIc2aouqgfgMwKo/QbpQCBhHYmoB4BHAPQGUAnACgAvCiE+NJQ5I1KmC4AtAN4D8IQQotRUVx6AZwGcDaAagGkAbhNCzLG4rlSdfuM039epVhnrd8iH1POadMgpJm9QmB1GDmlmby9mXOmq2Dg6jbsPnNYZj4/6O/q+T7v6jhOA7BheUhZ7X73b1rONyNK4di7eufjIaOjBOtUq4RtFjYGV9qqGjfmUW+p6N6wGbLcFxoOndUGPVnXQR2I79bI+rdGpcS3HvmBnR+ykRbcKbSYDy+JMpmMchz++spflTq+OUcniJrA3qFkFE+8eILWgPaNrU7w2dhk6Nq4V9d9ywquZ49Ft69mb5hjGNhkH8pkPHI/Nu4rQpam7nfPxXRrheJvkZ3YcLFHvDzceg6krt+GS3q2U6vaKm8b50t6t8OHk1TikWa3od9itRR66+aCEcsLJvDYRrjq2DSYu32prb59u+L78IKJTAEyCJqg/COB2AKMBtDCVGQFgO4CbIv8/BOBFU11ZAEYBuADAqwDuAtAIwHgiamsqK1Vnsnnw9C6oVjkbNw9s71ud5pTxuZWypJ2H/MT48B/fuZFjxrkyhYnCqKFxyjZ3Zd82mHLvcdH3brsZstp6s525ypZp7aqVpCYLI1UsnB0vO6Z1nMNMp8Y1HTXhVjhpumWpWjkbZ3dvLpWIJTuLcEx754VTdhbhSlPIvOcGdcVgB9veO0/qhNxKWcqaKBbYmUzHGKzATaOoGjpYdvepdrVKmHzPQPzfZT1StmNljOwjk7yvXo0qUsK6Kq8N7o6Ljz4Id57snkX80Oa1cdWxbZIWJtZJYL+mXxvcd2pnvH/pkfjkSnsHY1luPV6L8CNjSpNAvA1H+nVogJ9v6Ysvr0n8fsKArxp2IqoN4EMAbwohbnEoOhTAbAAnCSHKIufuAnAvEb0ihFgWKTcImpb+bCHEiEi5LwEsBfAwgIs91JlUeraui3kPn6gsxDlxzuHN8efSfIyYoyWRWPDISb7WL0/FwHzPKR0dBbryGKck5wG9fo0quGFAW+zaV4p+Lvb8TWpXRZsG1bEyfw8ussgMG9NayXnk7pM7oVuLPNzy+Ryl8wD1jHL3n9rZUuNco0oOfrqlb0zSoFE391WydezeMg9vD4mNh+xXprdEeeD0Lpi7vgB/rd4BwF3j1q5hDcx84ARUk9g6Nd6hH/GHGSbMGEOTugnsxuc/x807VJFU5w6pmVsJn17VC/tLygIRxGU5vWtTnN7Vm89N0Fhl076sTytc2bcNmtbOBRG5ZveV5br+bdGtpVy+gCZ5uVizba8v1zWTKdp1wH8N+2AAedA02yCimmRabhNRF2gmK2/pgnWENyLtOddwbBCAjQBG6geEEPkAvgRwFhFV8lCnZ+zSZbvt5gQhTBu1yakR1rWV80H1qqFNg+quMcErZ1cIWvUcIs/o3HlSJzx21iFSmoefb+mLmQ8c72pOZJal7WTr3ErZOLObfexu54uoFb/qWPnMsKoT4rmHN48Lo5jOPjjVq+RIae+KSiqGALuwogyTKZQq7F7KmhumK73b1vdN4MxE6lWPnQ8a1aqCh/91MJrlVfV9Z6RyThb6dWggZSL11pAj0KZ+dTx65sGuZQ9k/Jb0jgewGMCpRLQOwC4A24noaSLSJTY9HMMM44lCiI0A1hs+18vOFPEeZ9MB1ATQzlBOtk7PmD2udS7p7azZDYKDm8rHOg2K6lVyMO72/vj1v8e6anYOaVYLF/Zsicv6tJJKDqRClZxsR9MZHaP2u1ZuDqbcM1CqfpWBTFXDnihVHWITWzXFvCV6jcKCwW+CWjwMiZg0BTEJMUzYGNipIQA5R0vj88/PxoHH9QPaxijB6kvMm8mgU+NaGHtHf1x8dKtUNyXU+O102g6arfqH0BxFZwM4HcDdAHIB/BeAboS6yeL8TQCMe0lNAIy1KYdI2b8V64xCRAVWxw3ESJZW2/F/3X+8czKYgLi8T2sU7i9Fn4DCTMmSlUXIklArE5Fr8p6gMQrTx3duFOdBb0cPiS29RrWqYPOuIhzf2V27c+vxHfDauGV41yYTnxHd3McciUZnzO39cNNnszFzzY64z6zMQYwT9rCLjggk1KUsQYXcatewJqbeOxB5nJGUOQA45dAmGHbREWhR1z2ZWjrvsDGJc3jLOpj70In4/K+1+GDSasesqUz48FtgrwGgDoB7hBDPRI59S0Q1AFxPRI8D0EeVIovz90OLBKNT1aGc/rnxVaZOJWrl5uCm49qhU+NaaFG3Gu49pROe+nlx9PNUCOuA5mBzzynuTi1MBUbxVUa79N4lR2LGmh24ViKT4MsXdMfkFduisfSduOX49rimXxuprIufX30Uxvy9Bad1tXa2bJpXFWcc1tRSYLdSuBn9clOtgTZH4/ET2cUYw2QCdvkVzHRrkYePpq4JuDVMmKlaORuX9WntmMWcCSd+C+x6/MLPTMc/AXAegJ6GMlaSbq7hc70+u3LG66nUGUUIkWd1XCeiga99+4kdo8eu6dcWT/+ymDUVaYhRNpWRUwd2boSBEhpzADiqTT0cpZB8SDZFesOaubjQJTPicZ0a4uHvF1oeN1O/RoX/QKo10Kd1bYL5G3amtA0McyBxdvdmKNhXgs6N7ZMrMQwTTvwW2DcBOBjAZtNx/X0dVJitNEG8CUsTAJNN9VmpFvVjGw3lZOtMmFsGtsdLo5cFHpuU8RejNjmTHK5a1K2GCXcNQLXK2aickwUBYH9JmWXUnu4t6+CWge1RvUq255j/fnHFMa3RsGYVqRBsDMMkTlYW4YpjWLPKMOmI3wL7TGiOp80ArDQc17PO5APYEPn/SACz9AJE1DRSbo7hvDkAehMRmRxPewHYDWC5oZxsnQlzw4B26NYiD4dL2DYz4STZzqFBYxa+azkkT7n1hA5BN0eKStlZOOdw9yyDDMMwDHOg43eUmK8ir1foByJhHa8EsAfAVCHEQmiRZK42RI4BgOsAlAP4xnDsa2gOo2ca6qsPzbxmpBCiBAAU60yYStlZ6N+xoaNQxIQbmZTYDMMwDMMwYcBXDbsQYiYRDYeWrKghNG33aQBOAnCXEGJXpOidAL4H8CsRfQHgEAA3QoujvtRQ5dcApgIYTkRDAWwFcD20hcYjpsvL1skcwJx7eHPMWrsD10k4kjIMwzAMw4QBig9xnmCFRJUBPAjgEgCNoZnGvCiEeMtU7ixo2Uo7QzOVeR/AY0KIUlO5OgCeA3AWtGgw0wHcLoSYBROydSrcS0Ht2rVrFxQUeDmdCSlCCI5BzDAMwzBMqMjLy8POnTt3WgVF8V1gzyRYYGcYhmEYhmGSgZPAnpqc9gzDMAzDMAzDSMECO8MwDMMwDMOEGBbYGYZhGIZhGCbEsMDOMAzDMAzDMCGGBXaGYRiGYRiGCTEssDMMwzAMwzBMiGGBnWEYhmEYhmFCDAvsDMMwDMMwDBNiOHGSA0RUDoBq166d6qYwDMMwDMMwGczOnTsBQAgh4hTqLLA7QET6l7MzpQ1JjBqR190pbYU86dZeK/QVXrr2m0z4DdL5HtK9/wDp/f3rpPM9cB9KPenefoD7USqoDQBCCDJ/kJP8tqQV+lInL8Xt8AwRjQcAIUT/1LZEjnRrrxVEVACkb7/JkN9gPJCe95Du/QdI7+9fJ53vgftQ6kn39gPcj1KB/p1bwTbsDMMwDMMwDBNiWGBnGIZhGIZhmBDDAjvDMAzDMAzDhBgW2BmGYRiGYRgmxHCUGAcyweGCST7cb5hE4P7DJAr3IcYPuB8lH6fvnDXsDMMwDMMwDBNiWGBnGIZhGIZhmBDDJjEMwzAMwzAME2JYw84wDMMwDMMwIYYFdoZhGIZhGIYJMSywMwzDMAzDMEyIYYGdYRiGYRiGYUIMC+wMwzBpABH1JyJBRP1T3RaGYRgmuRyQAjsRXRqZ+Lqlui1MekFEd0b6zphUt4VJT3j8YRKBiLoS0edEtImIiohoLRG9R0StPdR1MhE9EkAzmZDC40/6ckAK7AyTAP8BsBpAfyJqkuK2MAxzAEFE5wOYCaAvgLcBXA/gMwBnA5hLRH0VqzwZwMO+NpJhmEBggZ1hJCGiLgAOA3AjgD0ALvC5/mp+1scwTOZARO0BfAhgCYBDhRAPCyHeE0LcDeBwALsBfEVEdVPYTIZhAoIFdgBE1JeIvopsLRYR0ToiepGIqprKfUhEBUTUgoi+J6LdRJRPREOJKDtV7WeSxn8AbAbwC4CRkfdRDDbGg4joaSLaHOkj3xBRY1PZ8UQ0h4h6EtFEItoH4K6k3QkTGohoNRF9aHF8PBGNT36LmJByB4CqAK4RQmw3fiCEWA1t/GgE4Br9OBF1IaKviWgrEe0jokVEdF/ksw8B3BL5X+h/ybkVJiyw/JM+5KS6ASHhPADVALwJYBuAngBuAtA88pmRSgB+AzAJ2gB6AoDbAayInM9kLhcC+FoIUUZEnwP4kYg6CCGWmso9BKAUwJMAmkGbFNsSUQ8hRImhXAMAPwL4BMBwAGsDvwOGYdKV0wGsEkJMsvn8KwDvADgNwFMRG+U/AewHMAzAOgAdIvU8CeAtAI0BnARgSKAtZ8IMyz9pAgvsGncLIfYZ3r9NRMsBPElELYUQRkGqGoDhQoinIu+HEdEsAFeAO2zGQkS9AbQG8EXk0G8AdkDTspttQGsDOFgIsTty7gIA/wdgcORVpymAK4QQ7wfYdIZh0hwiqg1tvBhpV0YIUURESwF0jhx6FUA5gMOFEOsNdVGk/BQiWgzgJCHEx4E1ngk7LP+kCWwSA8DYWYmoOhHVBzAZAAHobnHKW6b3EwC0Ca6FTAgYDGADgIkAENGUfxs5bub/dGE9wqfQhPtTTOX2AvjI/6YyDJNh1Iy8FrqUKwRQi4gaADgGwLtGYR0AhBBs9sJEYfknfWCBHQARtYzYZ22H5riTD+CPyMe1TcV3m+0HoQljdQJuJpMiiCgHwPkAxkMzbWlHRO0ATAHQjoh6mk5ZZnwjhCiFFlmmlancepOJDMMwjBW6oF7TsZT2eSEqBKgFgbWIyQhY/kkfDniTmIizxO8A6gJ4BsBiaBFAmkHzyDcvasqS2T4mFJwAzd78PzA5mkYYDGC6h3r3uRdhDgDsNJ7Z4PGGASCE2ElEmwB0tStDRFWg2ajPTFrDmLSG5Z/04oAX2AEcCm2Qu0QIMVw/SEQnpK5JTMj4D4D1AG61+GwIgH8T0e2GY+2NBSIa+lbQBkaGMbMDQJ7F8YMArExuU5gQMwrAlUTUWwgx2eLzQQByI+X0fnOIS51sHnNgw/JPGsEmMRUrRtIPRJxybklNc5gwEYmNfiaAH4QQX5v/oCUvaQzgOMNplxBRDcP7wdC2DH9OWsOZdGIFgKOIqLJ+gIhOB9AidU1iQshQRCK+EFGMCQIRtQTwLLSws28JIfKh+dtcSUTNTWXJ8HZP5FhegO1mwgvLP2kEa9i1LaAVAIYSUTMAuwCcC7bJYjTOBFADWvhFK8ZCM235D7QtRADYCeBPIvo/VIR1XAAtfCPDmHkXmnb0FyL6EkBbABdBG5cYBgAghFhCRJdDCwE7n4jehRYKtj2AqwFUBnCawcb4FmhhHWcR0dsA1gBoB80ZtU+kjG4+8woR/QqgTAjxeVJuiAkDLP+kEQeqhl1fTZZFnP7+BWAOgHuhhehbBuDi1DSNCRmDoUVzGWv1YcTDfjS01OC5kcOPQjN/uR/ADdC2qE9iB1MmQnT8AQAhxK/QYhl3APASgKOhxcpeb3Uyc+AihPgMQA9ocbCvhRZffQi0cI+HCSH+NJSdBaA3NOf4GwC8DK1ffW+ocmTk+MnQIlZ9FvxdMCmG5Z80hQ7ECE9EdDO0QaqVEGJNqtvDZAZE1B/AOABnCyFGpLQxTGjh8YdhmFTB40/6cqBq2HtAC321LtUNYRjmgIPHH4ZhUgWPP2nKAWXDTkTnAugPzd54mBCiPLUtYhjmQIHHH4ZhUgWPP+nPASWwQ/OyrwngHQB3pLgtDMMcWPD4wzBMquDxJ805IG3YGYZhGIZhGCZdOFBt2BmGYRiGYRgmLWCBnWEYhmEYhmFCTMYJ7ETUg4heJ6JFRLSHiNYS0edE1M6ibG8imkhEe4noHyJ6OZLZ0limCRE9TUTjiKiQiEQkfJ9bOw6K1CuIqJtvN8gwDMMwDGNBKmUgIlod+dz893Qwd3tgkYlOp3dDy+L2FYB50NLG3whgNhH1FEL8DQARIXoMgIUAbgPQHJojRhtoiQR0OkbqXB6pr7dkO4YCYC9shmEYhmGSRaploJnQEsAZWeD5bpgomSiwvwBgsBCiWD9ARF8AmA+t010aOfwkgG0A+gshdkfKrQbwDhEdJ4TQM1vOBFBfCLGNiM4C8J1bAyKrzzMAPAct2yXDMAzDMEzQpFoGWi+E+Nine2EMZJxJjBBisrGjRo4tg7aK7AwARFQLwAkAhusdNcJwALsBnG84t1AIsU32+kSUDS2L2GvQVqQMwzAMwzCBk2oZKFJ/FbNpDZM4GSewW0FEBKARgK2RQ4dC212YYSwX6eRzAHRP4HLXAGgG4LEE6mAYhmEYhkmYJMtAJwLYA2APEa0goqsTqIsxcEAI7NAyezUD8GXkfZPI6yaLspsANPVyESKqC01Qf0QIUeClDoZhGIZhGB9JigwEzcb9YQDnArgK2gLhLSK6x2N9jIFMtGGPgYg6AXgdwEQAH0UOV428Flmcst/wuSqPAtgCYJjH8xmGYRiGYXwhmTKQEOIM07U/iFz3QSJ6Uwix00u9jEZGa9iJqDGAUQB2ADhPCKFHbdkXea1icVqu4XOVax0C4FoAtwshSj00l2EYhmEYxheSKQNZIYQogxYxphqAo/2o80AmYzXsRFQbwM8AagPoI4T4x/Cxvg3UJO5E7dhGD5d8EsAsAIuIqFXkWP3Ia1Mi2iaEWOehXoZhGIZhGGlSIAPZocs9dX2s84AkIzXsRJQL4AcAHQCcLoRYYiqyAEApgCNN51UG0A2a04UqLQH0ALDK8Pdc5LNRAP7yUCfDMAzDMIw0KZKB7GgTec33sc4DkozTsEfCKn4BbfvlTCHEVHMZIcROIhoNYAgRPWkIazQEQA1oCQdUuRXaStbIcQBugpaU4G8PdTIMwzAMw0iRKhkoEnSjwGB2oy8c7gRQCGCK8s0wMWScwA7geWhJi34AUJeILjJ8tlsIMSLy//0AJgMYT0TvQsvydTuAn4UQo40VEtEDkX87R16HENEx0DrnawAghBhnbggR5UX+HSeEmJPgfTEMwzAMwziREhkocs37iehrAKsB1ANwCTQt/3WmeO+MB0gIkeo2+AoRjQfQz+bjNUKIVoayxwB4BsDhAHZBW5XeK4TYY6rT7kuKqc+iLZcC+ABAdxbYGYZhGIYJklTJQER0BIBHoMVwbwAtAs0sAEOFED96uxvGSMYJ7AzDMAzDMAyTSWSk0ynDMAzDMAzDZAossDMMwzAMwzBMiGGBnWEYhmEYhmFCDAvsDMMwDMMwDBNiWGBnGIZhGIZhmBDDAjvDMAzDMAzDhBgW2BmGYRiGYRgmxLDAzjAMwzAMwzAhhgV2hmGYNIeIVkcyHKY1RPQIEQkiapXqtjAMw4QJFtgZhmEOcIjov0R0aZKudRYRPZKMazEMw2QKJIRIdRsYhmGYBCCi1QBWCyH6p+J8xWt9COASIQRZfJYDIAdAkeDJiWEYJkpOqhvAMAzDMAAghCgFUJrqdjAMw4QNNolhGIZJE4ioBRF9SUQ7iWgXEf1ARG1tyv6biL4norVEVEREW4loBBF1NZUTAA4C0C9iPy7MduREdCQRfRepo4iIlhDR/RGNuEr7xwO4RL+u4e/SyLE4G3bDsS5E9BIRbSKivUQ0hog6RsqcQ0SziGhfxJ7/apvrH09EvxFRARHtJ6J5RHStyj0wDMOkAtawMwzDpAFElAfgTwAtAAwDsAhAPwDjAFS1OOVGANsAvA3gHwBtAVwNYBIRHS6EWBYpNwTAiwC2AnjCcH5+5LqnAfgWwHIAzwPYDuBoAI8C6AbgPIXbeAKaoqhv5Lo6kyXO/T8AuwE8CaABgNsB/EpEDwJ4FsCbAN4HcAWAt4hokRBion5yRIgfBmBqpB17AJwA4E0iaiuEuFPhPhiGYZIK27AzDMOkAUT0JIB7AVwuhPjAcPwlALcA+MNog05E1YUQe0x1dAYwB8B7QojrDcdXw8KGnYhyAawGsBTAcRGTFf2zWwG8AGCAEGK8wn18CHsb9kcAPAygtRBitenYjwDO0G3biehmAC8DKARwsBBiXeR4AwDrAHwnhLgwcqwJgFUAvhVCDDZd82Voi5v2QoiVsvfBMAyTTNgkhmEYJj04C8BmAMNNx5+xKqwL66RRi4jqQ9OaLwHQS/KaJwBoBOADAHlEVF//A/BTpMyJSnfhnVdMjqgTIq/f68I6AAgh9Htsbyg7CEAVAO8Z7yFyHz9AmwuPD7b5DMMw3mGTGIZhmPSgDYC/hBBlxoNCiE1EVGAuTETdATwGoD+A6qaPV0les3Pk9X2HMo0k60oUs/Z7R+TV6l52QLPL19HvY7RD/cm6D4ZhGGVYYGcYhskwiKglNHv3XdCE9iXQbLYFgJcA1JCtKvJ6JzRTGis2em2nImWKx8ni/4sBbLIpz+YwDMOEFhbYGYZh0oOVANoTUbZRyx6xz84zlT0bmlB+hhBinPEDIqoHoMhU3s6ZSXdM3SOEcNJOq5AKxyn9Prb6eB8MwzBJg23YGYZh0oOR0Mw2LjYdv9uirC7Qxzh2EtFVABpblN8NoK7F8V8BbAFwDxHFfU5EVYmopku7ra4Fq/oC5Etoi5T/EVFcRB0iqk1EVZLYHoZhGCVYw84wDJMePAtgMIB3iOgIAAuh2acfDS0ko5GfAewF8BERvQbNprsPgFMBrED82D8VwBVE9BiAvwGUA/hBCLGHiC4GMALAEiJ6H1p4xzwAnQCcA02bP17hPqZCi8ryBhGNAlACYJoQQtauXhkhxHoiug7AuwD+JqKPAKyBFh7yUGgOvV2gRcRhGIYJHSywMwzDpAFCiB1E1BdaKEVdy/4HgAEAxpjKriCiU6DFLL8PmsZ9ErS47a8BaGWq/n5oGvYboAnjBKA1NFOYX4moB4B7AFwETcjdAU3wfwHAPMVb+QxAdwAXQIvhngXgMsg7wnpCCPEBES0FcAeAa6Dd51Zo9v0PQotVzzAME0o4DjvDMAzDMAzDhBi2YWcYhmEYhmGYEMMmMQzDMExCEFENuIeKLIskNWIYhmEUYYGdYRiGSZQ7ADzsUmYN4m3nGYZhGAnYhp1hGIZJCCJqAy0TqxP7hBCTktEehmGYTIMFdoZhGIZhGIYJMex0yjAMwzAMwzAhhgV2hmEYhmEYhgkxLLAzDMMwDMMwTIhhgZ1hGIZhGIZhQsz/A0CNbbXsOfG8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the data from the year 2014 onwards\n",
    "data[\"demand\"].loc[\"2014\":].plot(figsize=[12, 5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "637cfca6-d85b-4bd8-8da9-fda81ac23133",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date_time'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[\"temperature\"].loc[\"2014\":].plot(figsize=[12, 5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "88ea37f2-a6be-4948-8a31-0a6a41405d7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date_time'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Demand on a single day\n",
    "data[\"demand\"].loc[\"2015-02-01\"].plot(figsize=[12, 5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f6693e28-3b7f-4b97-90b9-e387e9110084",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date_time'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Temperature on a single day\n",
    "data[\"temperature\"].loc[\"2015-02-01\"].plot(figsize=[12, 5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b747b7d4-c8f5-4d55-8f4e-8018f3fe6b2f",
   "metadata": {},
   "source": [
    "We can see that there is seasonality on different time scales (e.g., daily, weekly, yearly). We'll see how rolling window features can help capture information at these different time scales. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "318a42fa-152e-4778-911c-e9aa88f4fa41",
   "metadata": {},
   "source": [
    "See notebook 06 on MSTL in the Time Series Decomposition section where we go into a lot more detail to show that there is daily, weekly, and yearly seasonality."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "certified-occupation",
   "metadata": {},
   "source": [
    "# Computing rolling windows features using Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e43e3387-8ef6-4a87-9972-94f1ddba5833",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a copy of the data.\n",
    "df = data.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab077e61-2aac-402f-8a74-11d8a2d3739f",
   "metadata": {
    "tags": []
   },
   "source": [
    "We want to compute the rolling:\n",
    "- mean\n",
    "- standard deviation\n",
    "- median absolute deviation\n",
    "\n",
    "The median absolute deviation is not implemented natively in Pandas so we have to create it as a custom metric ourselves.\n",
    "\n",
    "Let's create a function to compute the median absolute deviation which is defined as: $MAD = median(|x_i - median(x)|)$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0e326ca6-6ef4-44bf-a6ea-cce4957944b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a custom metric for the MAD\n",
    "def mad(x):\n",
    "    return np.median(np.abs(x - np.median(x)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33c0377c-79f9-4f1e-89b2-1e5fa6a53cca",
   "metadata": {},
   "source": [
    "We'll use a window size of 24 hours to smooth over daily seasonality. Let's compute the rolling window features!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e0095646-701e-4266-bed4-eb83c1c27eef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand_window_24_mean</th>\n",
       "      <th>demand_window_24_std</th>\n",
       "      <th>demand_window_24_mad</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-01 01:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 02:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 03:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 04:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 05:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 20:00:00</th>\n",
       "      <td>8786.593557</td>\n",
       "      <td>957.615692</td>\n",
       "      <td>621.110944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 21:00:00</th>\n",
       "      <td>8764.566712</td>\n",
       "      <td>948.645664</td>\n",
       "      <td>655.453210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 22:00:00</th>\n",
       "      <td>8750.681279</td>\n",
       "      <td>952.771813</td>\n",
       "      <td>655.453210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 23:00:00</th>\n",
       "      <td>8744.571813</td>\n",
       "      <td>956.539865</td>\n",
       "      <td>685.465653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-01 00:00:00</th>\n",
       "      <td>8736.358080</td>\n",
       "      <td>957.637149</td>\n",
       "      <td>685.465653</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45240 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     demand_window_24_mean  demand_window_24_std  \\\n",
       "date_time                                                          \n",
       "2010-01-01 01:00:00                    NaN                   NaN   \n",
       "2010-01-01 02:00:00                    NaN                   NaN   \n",
       "2010-01-01 03:00:00                    NaN                   NaN   \n",
       "2010-01-01 04:00:00                    NaN                   NaN   \n",
       "2010-01-01 05:00:00                    NaN                   NaN   \n",
       "...                                    ...                   ...   \n",
       "2015-02-28 20:00:00            8786.593557            957.615692   \n",
       "2015-02-28 21:00:00            8764.566712            948.645664   \n",
       "2015-02-28 22:00:00            8750.681279            952.771813   \n",
       "2015-02-28 23:00:00            8744.571813            956.539865   \n",
       "2015-03-01 00:00:00            8736.358080            957.637149   \n",
       "\n",
       "                     demand_window_24_mad  \n",
       "date_time                                  \n",
       "2010-01-01 01:00:00                   NaN  \n",
       "2010-01-01 02:00:00                   NaN  \n",
       "2010-01-01 03:00:00                   NaN  \n",
       "2010-01-01 04:00:00                   NaN  \n",
       "2010-01-01 05:00:00                   NaN  \n",
       "...                                   ...  \n",
       "2015-02-28 20:00:00            621.110944  \n",
       "2015-02-28 21:00:00            655.453210  \n",
       "2015-02-28 22:00:00            655.453210  \n",
       "2015-02-28 23:00:00            685.465653  \n",
       "2015-03-01 00:00:00            685.465653  \n",
       "\n",
       "[45240 rows x 3 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = (\n",
    "    df[\"demand\"]\n",
    "    .rolling(window=24) # Pick window size.\n",
    "    .agg([\"mean\", \"std\", mad]) # Pick statistics.\n",
    "    .shift(freq=\"1H\") # Lag by 1 hour to avoid data leakage.\n",
    ")  \n",
    "\n",
    "result = result.add_prefix(\"demand_window_24_\")\n",
    "\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba8edefa-89dd-4848-9b12-71f6384a3298",
   "metadata": {},
   "source": [
    "Let's join this back to the original dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "24dee532-5f4a-4838-a245-59e3734cb47d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand</th>\n",
       "      <th>temperature</th>\n",
       "      <th>demand_window_24_mean</th>\n",
       "      <th>demand_window_24_std</th>\n",
       "      <th>demand_window_24_mad</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-01 00:00:00</th>\n",
       "      <td>8314.448682</td>\n",
       "      <td>21.525</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 01:00:00</th>\n",
       "      <td>8267.187296</td>\n",
       "      <td>22.400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 02:00:00</th>\n",
       "      <td>7394.528444</td>\n",
       "      <td>22.150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 03:00:00</th>\n",
       "      <td>6952.047520</td>\n",
       "      <td>21.800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 04:00:00</th>\n",
       "      <td>6867.199634</td>\n",
       "      <td>20.250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 19:00:00</th>\n",
       "      <td>9596.777060</td>\n",
       "      <td>28.350</td>\n",
       "      <td>8802.565712</td>\n",
       "      <td>974.759690</td>\n",
       "      <td>712.857278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 20:00:00</th>\n",
       "      <td>8883.230296</td>\n",
       "      <td>22.200</td>\n",
       "      <td>8786.593557</td>\n",
       "      <td>957.615692</td>\n",
       "      <td>621.110944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 21:00:00</th>\n",
       "      <td>8320.260550</td>\n",
       "      <td>18.900</td>\n",
       "      <td>8764.566712</td>\n",
       "      <td>948.645664</td>\n",
       "      <td>655.453210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 22:00:00</th>\n",
       "      <td>8110.055916</td>\n",
       "      <td>18.900</td>\n",
       "      <td>8750.681279</td>\n",
       "      <td>952.771813</td>\n",
       "      <td>655.453210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 23:00:00</th>\n",
       "      <td>8519.368752</td>\n",
       "      <td>18.900</td>\n",
       "      <td>8744.571813</td>\n",
       "      <td>956.539865</td>\n",
       "      <td>685.465653</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45240 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          demand  temperature  demand_window_24_mean  \\\n",
       "date_time                                                              \n",
       "2010-01-01 00:00:00  8314.448682       21.525                    NaN   \n",
       "2010-01-01 01:00:00  8267.187296       22.400                    NaN   \n",
       "2010-01-01 02:00:00  7394.528444       22.150                    NaN   \n",
       "2010-01-01 03:00:00  6952.047520       21.800                    NaN   \n",
       "2010-01-01 04:00:00  6867.199634       20.250                    NaN   \n",
       "...                          ...          ...                    ...   \n",
       "2015-02-28 19:00:00  9596.777060       28.350            8802.565712   \n",
       "2015-02-28 20:00:00  8883.230296       22.200            8786.593557   \n",
       "2015-02-28 21:00:00  8320.260550       18.900            8764.566712   \n",
       "2015-02-28 22:00:00  8110.055916       18.900            8750.681279   \n",
       "2015-02-28 23:00:00  8519.368752       18.900            8744.571813   \n",
       "\n",
       "                     demand_window_24_std  demand_window_24_mad  \n",
       "date_time                                                        \n",
       "2010-01-01 00:00:00                   NaN                   NaN  \n",
       "2010-01-01 01:00:00                   NaN                   NaN  \n",
       "2010-01-01 02:00:00                   NaN                   NaN  \n",
       "2010-01-01 03:00:00                   NaN                   NaN  \n",
       "2010-01-01 04:00:00                   NaN                   NaN  \n",
       "...                                   ...                   ...  \n",
       "2015-02-28 19:00:00            974.759690            712.857278  \n",
       "2015-02-28 20:00:00            957.615692            621.110944  \n",
       "2015-02-28 21:00:00            948.645664            655.453210  \n",
       "2015-02-28 22:00:00            952.771813            655.453210  \n",
       "2015-02-28 23:00:00            956.539865            685.465653  \n",
       "\n",
       "[45240 rows x 5 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.join(result, how=\"left\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb11f5e8-54c9-4e9a-b2cd-b5c4e9ee0d68",
   "metadata": {},
   "source": [
    "The `min_periods` argument can be used to allow smaller window sizes to be applied at the start of the time series. This is one method to reduce the amount of missing data at the start of the time series. Alternatively, we could drop the missing data altogether."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c7d19c6c-0bd9-43a0-9ce7-9c31317bbcb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand</th>\n",
       "      <th>demand_window_24_mean</th>\n",
       "      <th>demand_window_24_min_periods_mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-01 00:00:00</th>\n",
       "      <td>8314.448682</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 01:00:00</th>\n",
       "      <td>8267.187296</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8314.448682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 02:00:00</th>\n",
       "      <td>7394.528444</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8290.817989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 03:00:00</th>\n",
       "      <td>6952.047520</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7992.054807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 04:00:00</th>\n",
       "      <td>6867.199634</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7732.052986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 19:00:00</th>\n",
       "      <td>9596.777060</td>\n",
       "      <td>8802.565712</td>\n",
       "      <td>8802.565712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 20:00:00</th>\n",
       "      <td>8883.230296</td>\n",
       "      <td>8786.593557</td>\n",
       "      <td>8786.593557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 21:00:00</th>\n",
       "      <td>8320.260550</td>\n",
       "      <td>8764.566712</td>\n",
       "      <td>8764.566712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 22:00:00</th>\n",
       "      <td>8110.055916</td>\n",
       "      <td>8750.681279</td>\n",
       "      <td>8750.681279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 23:00:00</th>\n",
       "      <td>8519.368752</td>\n",
       "      <td>8744.571813</td>\n",
       "      <td>8744.571813</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45240 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          demand  demand_window_24_mean  \\\n",
       "date_time                                                 \n",
       "2010-01-01 00:00:00  8314.448682                    NaN   \n",
       "2010-01-01 01:00:00  8267.187296                    NaN   \n",
       "2010-01-01 02:00:00  7394.528444                    NaN   \n",
       "2010-01-01 03:00:00  6952.047520                    NaN   \n",
       "2010-01-01 04:00:00  6867.199634                    NaN   \n",
       "...                          ...                    ...   \n",
       "2015-02-28 19:00:00  9596.777060            8802.565712   \n",
       "2015-02-28 20:00:00  8883.230296            8786.593557   \n",
       "2015-02-28 21:00:00  8320.260550            8764.566712   \n",
       "2015-02-28 22:00:00  8110.055916            8750.681279   \n",
       "2015-02-28 23:00:00  8519.368752            8744.571813   \n",
       "\n",
       "                     demand_window_24_min_periods_mean  \n",
       "date_time                                               \n",
       "2010-01-01 00:00:00                                NaN  \n",
       "2010-01-01 01:00:00                        8314.448682  \n",
       "2010-01-01 02:00:00                        8290.817989  \n",
       "2010-01-01 03:00:00                        7992.054807  \n",
       "2010-01-01 04:00:00                        7732.052986  \n",
       "...                                                ...  \n",
       "2015-02-28 19:00:00                        8802.565712  \n",
       "2015-02-28 20:00:00                        8786.593557  \n",
       "2015-02-28 21:00:00                        8764.566712  \n",
       "2015-02-28 22:00:00                        8750.681279  \n",
       "2015-02-28 23:00:00                        8744.571813  \n",
       "\n",
       "[45240 rows x 3 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = (\n",
    "    df[\"demand\"]\n",
    "    .rolling(window=24, min_periods=1) # Pick window size.\n",
    "    .agg([\"mean\", \"std\", mad]) # Pick statistics.\n",
    "    .shift(freq=\"1H\") # Lag by 1 hour to avoid data leakage.\n",
    ")  \n",
    "\n",
    "result = result.add_prefix(\"demand_window_24_min_periods_\")\n",
    "\n",
    "df = df.join(result, how=\"left\")\n",
    "df[[\"demand\", \"demand_window_24_mean\", \"demand_window_24_min_periods_mean\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cf1d66b-cdbe-437d-8876-e4c70208d2b0",
   "metadata": {},
   "source": [
    "# Using Feature-engine"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5339d62-2669-4160-97e3-635e1ccadf0d",
   "metadata": {},
   "source": [
    "Let's see how we can extract window features using the Feature-engine library."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2da697ad-466f-4327-ab1b-4f000d9d2596",
   "metadata": {},
   "outputs": [],
   "source": [
    "from feature_engine.timeseries.forecasting import WindowFeatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9c7f5c53-5a75-41fd-af42-09c73131b003",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a copy of the data.\n",
    "df = data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b566e12e-53ba-40a3-8d70-d2b12dd085cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand</th>\n",
       "      <th>temperature</th>\n",
       "      <th>demand_window_24_mean</th>\n",
       "      <th>demand_window_24_std</th>\n",
       "      <th>temperature_window_24_mean</th>\n",
       "      <th>temperature_window_24_std</th>\n",
       "      <th>demand_window_168_mean</th>\n",
       "      <th>demand_window_168_std</th>\n",
       "      <th>temperature_window_168_mean</th>\n",
       "      <th>temperature_window_168_std</th>\n",
       "      <th>demand_window_8760_mean</th>\n",
       "      <th>demand_window_8760_std</th>\n",
       "      <th>temperature_window_8760_mean</th>\n",
       "      <th>temperature_window_8760_std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-01 00:00:00</th>\n",
       "      <td>8314.448682</td>\n",
       "      <td>21.525</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 01:00:00</th>\n",
       "      <td>8267.187296</td>\n",
       "      <td>22.400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 02:00:00</th>\n",
       "      <td>7394.528444</td>\n",
       "      <td>22.150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 03:00:00</th>\n",
       "      <td>6952.047520</td>\n",
       "      <td>21.800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 04:00:00</th>\n",
       "      <td>6867.199634</td>\n",
       "      <td>20.250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 19:00:00</th>\n",
       "      <td>9596.777060</td>\n",
       "      <td>28.350</td>\n",
       "      <td>8802.565712</td>\n",
       "      <td>974.759690</td>\n",
       "      <td>21.856250</td>\n",
       "      <td>5.141695</td>\n",
       "      <td>9670.463454</td>\n",
       "      <td>1539.992921</td>\n",
       "      <td>21.085714</td>\n",
       "      <td>4.840353</td>\n",
       "      <td>9169.130177</td>\n",
       "      <td>1597.845042</td>\n",
       "      <td>16.279344</td>\n",
       "      <td>5.272056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 20:00:00</th>\n",
       "      <td>8883.230296</td>\n",
       "      <td>22.200</td>\n",
       "      <td>8786.593557</td>\n",
       "      <td>957.615692</td>\n",
       "      <td>22.216667</td>\n",
       "      <td>5.285145</td>\n",
       "      <td>9654.616819</td>\n",
       "      <td>1526.838185</td>\n",
       "      <td>21.069048</td>\n",
       "      <td>4.810218</td>\n",
       "      <td>9169.143383</td>\n",
       "      <td>1597.848099</td>\n",
       "      <td>16.280348</td>\n",
       "      <td>5.273518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 21:00:00</th>\n",
       "      <td>8320.260550</td>\n",
       "      <td>18.900</td>\n",
       "      <td>8764.566712</td>\n",
       "      <td>948.645664</td>\n",
       "      <td>22.360417</td>\n",
       "      <td>5.233421</td>\n",
       "      <td>9638.018555</td>\n",
       "      <td>1519.920008</td>\n",
       "      <td>21.031845</td>\n",
       "      <td>4.776845</td>\n",
       "      <td>9169.122487</td>\n",
       "      <td>1597.850641</td>\n",
       "      <td>16.280713</td>\n",
       "      <td>5.273817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 22:00:00</th>\n",
       "      <td>8110.055916</td>\n",
       "      <td>18.900</td>\n",
       "      <td>8750.681279</td>\n",
       "      <td>952.771813</td>\n",
       "      <td>22.385417</td>\n",
       "      <td>5.214580</td>\n",
       "      <td>9624.108291</td>\n",
       "      <td>1521.229942</td>\n",
       "      <td>20.989583</td>\n",
       "      <td>4.764018</td>\n",
       "      <td>9169.122190</td>\n",
       "      <td>1597.850799</td>\n",
       "      <td>16.280691</td>\n",
       "      <td>5.273805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 23:00:00</th>\n",
       "      <td>8519.368752</td>\n",
       "      <td>18.900</td>\n",
       "      <td>8744.571813</td>\n",
       "      <td>956.539865</td>\n",
       "      <td>22.416667</td>\n",
       "      <td>5.190285</td>\n",
       "      <td>9613.687286</td>\n",
       "      <td>1525.589244</td>\n",
       "      <td>20.941667</td>\n",
       "      <td>4.744151</td>\n",
       "      <td>9169.133719</td>\n",
       "      <td>1597.842792</td>\n",
       "      <td>16.280696</td>\n",
       "      <td>5.273808</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45240 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          demand  temperature  demand_window_24_mean  \\\n",
       "date_time                                                              \n",
       "2010-01-01 00:00:00  8314.448682       21.525                    NaN   \n",
       "2010-01-01 01:00:00  8267.187296       22.400                    NaN   \n",
       "2010-01-01 02:00:00  7394.528444       22.150                    NaN   \n",
       "2010-01-01 03:00:00  6952.047520       21.800                    NaN   \n",
       "2010-01-01 04:00:00  6867.199634       20.250                    NaN   \n",
       "...                          ...          ...                    ...   \n",
       "2015-02-28 19:00:00  9596.777060       28.350            8802.565712   \n",
       "2015-02-28 20:00:00  8883.230296       22.200            8786.593557   \n",
       "2015-02-28 21:00:00  8320.260550       18.900            8764.566712   \n",
       "2015-02-28 22:00:00  8110.055916       18.900            8750.681279   \n",
       "2015-02-28 23:00:00  8519.368752       18.900            8744.571813   \n",
       "\n",
       "                     demand_window_24_std  temperature_window_24_mean  \\\n",
       "date_time                                                               \n",
       "2010-01-01 00:00:00                   NaN                         NaN   \n",
       "2010-01-01 01:00:00                   NaN                         NaN   \n",
       "2010-01-01 02:00:00                   NaN                         NaN   \n",
       "2010-01-01 03:00:00                   NaN                         NaN   \n",
       "2010-01-01 04:00:00                   NaN                         NaN   \n",
       "...                                   ...                         ...   \n",
       "2015-02-28 19:00:00            974.759690                   21.856250   \n",
       "2015-02-28 20:00:00            957.615692                   22.216667   \n",
       "2015-02-28 21:00:00            948.645664                   22.360417   \n",
       "2015-02-28 22:00:00            952.771813                   22.385417   \n",
       "2015-02-28 23:00:00            956.539865                   22.416667   \n",
       "\n",
       "                     temperature_window_24_std  demand_window_168_mean  \\\n",
       "date_time                                                                \n",
       "2010-01-01 00:00:00                        NaN                     NaN   \n",
       "2010-01-01 01:00:00                        NaN                     NaN   \n",
       "2010-01-01 02:00:00                        NaN                     NaN   \n",
       "2010-01-01 03:00:00                        NaN                     NaN   \n",
       "2010-01-01 04:00:00                        NaN                     NaN   \n",
       "...                                        ...                     ...   \n",
       "2015-02-28 19:00:00                   5.141695             9670.463454   \n",
       "2015-02-28 20:00:00                   5.285145             9654.616819   \n",
       "2015-02-28 21:00:00                   5.233421             9638.018555   \n",
       "2015-02-28 22:00:00                   5.214580             9624.108291   \n",
       "2015-02-28 23:00:00                   5.190285             9613.687286   \n",
       "\n",
       "                     demand_window_168_std  temperature_window_168_mean  \\\n",
       "date_time                                                                 \n",
       "2010-01-01 00:00:00                    NaN                          NaN   \n",
       "2010-01-01 01:00:00                    NaN                          NaN   \n",
       "2010-01-01 02:00:00                    NaN                          NaN   \n",
       "2010-01-01 03:00:00                    NaN                          NaN   \n",
       "2010-01-01 04:00:00                    NaN                          NaN   \n",
       "...                                    ...                          ...   \n",
       "2015-02-28 19:00:00            1539.992921                    21.085714   \n",
       "2015-02-28 20:00:00            1526.838185                    21.069048   \n",
       "2015-02-28 21:00:00            1519.920008                    21.031845   \n",
       "2015-02-28 22:00:00            1521.229942                    20.989583   \n",
       "2015-02-28 23:00:00            1525.589244                    20.941667   \n",
       "\n",
       "                     temperature_window_168_std  demand_window_8760_mean  \\\n",
       "date_time                                                                  \n",
       "2010-01-01 00:00:00                         NaN                      NaN   \n",
       "2010-01-01 01:00:00                         NaN                      NaN   \n",
       "2010-01-01 02:00:00                         NaN                      NaN   \n",
       "2010-01-01 03:00:00                         NaN                      NaN   \n",
       "2010-01-01 04:00:00                         NaN                      NaN   \n",
       "...                                         ...                      ...   \n",
       "2015-02-28 19:00:00                    4.840353              9169.130177   \n",
       "2015-02-28 20:00:00                    4.810218              9169.143383   \n",
       "2015-02-28 21:00:00                    4.776845              9169.122487   \n",
       "2015-02-28 22:00:00                    4.764018              9169.122190   \n",
       "2015-02-28 23:00:00                    4.744151              9169.133719   \n",
       "\n",
       "                     demand_window_8760_std  temperature_window_8760_mean  \\\n",
       "date_time                                                                   \n",
       "2010-01-01 00:00:00                     NaN                           NaN   \n",
       "2010-01-01 01:00:00                     NaN                           NaN   \n",
       "2010-01-01 02:00:00                     NaN                           NaN   \n",
       "2010-01-01 03:00:00                     NaN                           NaN   \n",
       "2010-01-01 04:00:00                     NaN                           NaN   \n",
       "...                                     ...                           ...   \n",
       "2015-02-28 19:00:00             1597.845042                     16.279344   \n",
       "2015-02-28 20:00:00             1597.848099                     16.280348   \n",
       "2015-02-28 21:00:00             1597.850641                     16.280713   \n",
       "2015-02-28 22:00:00             1597.850799                     16.280691   \n",
       "2015-02-28 23:00:00             1597.842792                     16.280696   \n",
       "\n",
       "                     temperature_window_8760_std  \n",
       "date_time                                         \n",
       "2010-01-01 00:00:00                          NaN  \n",
       "2010-01-01 01:00:00                          NaN  \n",
       "2010-01-01 02:00:00                          NaN  \n",
       "2010-01-01 03:00:00                          NaN  \n",
       "2010-01-01 04:00:00                          NaN  \n",
       "...                                          ...  \n",
       "2015-02-28 19:00:00                     5.272056  \n",
       "2015-02-28 20:00:00                     5.273518  \n",
       "2015-02-28 21:00:00                     5.273817  \n",
       "2015-02-28 22:00:00                     5.273805  \n",
       "2015-02-28 23:00:00                     5.273808  \n",
       "\n",
       "[45240 rows x 14 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create window features using the transformer.\n",
    "transformer = WindowFeatures(\n",
    "    variables=[\"demand\", \"temperature\"],\n",
    "    functions=[\"mean\", \"std\"],\n",
    "    window=[24, 24 * 7, 24 * 365], # Day, week, year.\n",
    "    freq=\"1H\",\n",
    ")\n",
    "\n",
    "df = transformer.fit_transform(df)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b4a21c1-6b98-497a-a81d-6b3ae417c8bd",
   "metadata": {},
   "source": [
    "Let's look at the rolling window mean of the demand."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "71e2b068-c99e-4827-8aba-72f84d078f64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Time')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EF4TnAv9WSj1Oue/t596AN1rrfUqpjzFSkYCR3iBcIrnPIhmjseJjDDPoKRjms82AGyj374wKrfVKz/P6VuAHpdRUDJ/BWzGiqJ5SoV4LQg1DBDlBEKoKTwD/xNDKnam1XqCU6oERqOEWjMAT6zCCo1SmaZ4FrfUopdQBDEHzKQyNymiM1e2uGOHaw8ErpBUCc0zluRjCThpxEOS01muVUr0wruFtGBrGrzFMrezyul2NoTka6NknH0PAfkRrvdSm/g8Ygpx/37/HEFDma62D5j+LNVrrEUqpBRiC550YY8lrtnq7qd5apdR5GIL6fzG0FrMxNKfjMXykYt23z5VSZ2NM/O/DmLCvAG7UWgeNjhhG20s8wVsexFg0uBlDUNyAIcAFXQzRWu9XSp0O3IORp+wijNQRWzD8Wl831S1RSp3rqfsvjGtYhGE2OMlUb7YycjHejGG6WAvjHo/KhFhr/ZlSqifG7/VvjAiPOzDuI7vxaeYhDI3cfzBSDiiMADT5pjoTMQS5NRjjPtx+RXSfhTtGY8jdGGPB+7tuxjjX+RiCXUW4A2PhbRDGs3E1xjXugAhyghARKoZWOYIgCIIDnlX3WzHyL/2V6P4IglBxPP5x84D/aq1HJbo/giDULESQEwRBiCFKqUz/EOse/5yVGMEKTkhMzwRBiDVKqXcwTIvbyAKNIAiVTUKDnSilmiulnlJK5SilDiqltFKqj029DZ5t/n9P2dRtoJSaqJTapZTKV0r9oJQ62eH4/ZRSi5RSRUqpTUqpYZ7cKVG3KQhCjaePUmqpUmqEUuompdQTGL4fdTHyMgmCUIVRStVRSl3l8Z27BiNhuwhxgiBUOon2kTsGw59lDUbo6h5B6i7EyNVixmIzr5RKAb7ESCL8LIZT7i3ALKVUF631WlPd8zAirv2AYZ9+AvAoRm6m26JpUxAEAeN5tha4CSPBbhGwABgVZZh3QRCSi6bA+xhRLT/GPtKkIAhC3EmoaaVSqh6Q7on01h8jMteZWutZfvU2YCSI7R+ivSswklderLX+xFPWFCNa3Oda6+tMdZdhTLC6eZNjKqVGYjh9d/RGAoukTUEQBEEQBEEQhMogoRo5rfXBSOorpTKAVK11gUOVyzBC8vrCCWutd3nCIv9TKZWmtS5VSh2HkXhysFeI8/AyRpSqSzGizYXdZoTnUYZh1nogkv0EQRAEQRAEQagx1AfcWmtbmS3RppWRcC5GyN9UpdQ64Gmt9US/OqcAC20S5P6KEeb2KIywzd7wtgvMlbTW25RSW7CGvw23zUhIAVR2dnZ2hPsJgiAIgiAIglAD2L9/PwSJaVJVBLnfMXK+rMKwTb8JmKCUaqS1Ngc8aY59XqXtnv8tMISu5n7l/nVbRNGmD6VUntOJeKtkZ2eTlxeqmiAIgiAIgiAINZEGDRqwf/9+Rwu+KiHIaa37mb8rpSZhJBt9RCn1itZ6v2dTFkZSTX+KTNvN/53q1jZ9D7dNQRAEQRAEQRCESiGh6QeixePXNhZD4DrNtKkQyLDZJdO03fzfqW6h6Xu4bZr71yDYH7Dffx9BEARBEARBEIRwqZKCnIfNnv+NTGXbKTebNOMt22aqR5C620zfw21TEARBEARBEAShUqjKgtyRnv+7TGVLgC5KKeVXtztGvpc1pnoAXc2VlFItgFam7ZG0KQiCIAiCIAiCUCkkvSCnlGrkScptLssE7gMOAnNMmz7GCD5ykaluE+By4FNvmgCt9TJgJTBIKZVq2n8I4AamRtqmIAiCIAiCIAhCZZHwYCdKqYc9H4/1/L9WKdUTyNNajwf6AQ8ppT4GNgCNgQHA0cAQrfUhU3MfA3OBd5RSzwK7gVswBNbhfoe+D/gMmKGUmgJ0Am4FJmitV0XZZkzJz8/nwIEDlJWV4Xa743koQRCECpGSkkJmZiZNmjQh0IBBEARBEIRYowLTo1VyB5Ry6sBGrXU7pVQXDIHpFIzUA8XAIuBZrfUXNu01BEYD/TEiSv4K3KO1XmRTtz8wDEOI3AW8CTyutS6Lts1wUErlZWdnZzulH3C73Wzbto2DBw+SkpJCWloaqamptnUFQRCSAZfLRXFxMfXq1aNly5YizAmCIAhCBfGkH9jvCZYYQMIFuZpIKEFu3759/PXXXzRp0oTGjRuTkpL0FrCCIAjs3buXHTt20KRJE5o2bZro7giCIAhClSaUICcSQhJy6NAh0tPTadKkiQhxgiBUGRo1akRGRgZFRUWhKwuCIAiCUCFESkhC3G43tWrVEtMkQRCqHKmpqeLTKwiCIAiVgAhygiAIgiAIgiAIVQwR5ARBEARBEARBEKoYIsgJgiAIgiAIgiBUMUSQE5KG4cOHV2u/wA0bNqCU4q233or7sfr06UOfPn2Svk1BEARBSCRut0RvF6ouIsgJglAlWblyJffffz8nn3wy9erVo3nz5lxwwQUsWhQ8vaPL5eLEE09EKcXYsWMrp7OCIAhC0vHuvI10Gj6Dr5duT3RXBCEqRJAThGrIt99+y7fffpvobsSV119/nddee42uXbsyZswY7r77blauXEn37t3Jyclx3O/VV19l3bp1ldhTQRAEIRl5aPofFJS4uHPKkkR3RRCiQgQ5QaiGpKenk56enuhuxJV//vOfbN68mddff51BgwZx3333MW/ePBo2bMiIESNs99m7dy+PPvoo999/fyX3VhAEQUgm/ti63/e5uExSpghVExHkhITw888/83//939kZmbSvn17JkyYYFtv0qRJdO7cmaysLJo0acKAAQPYsWOHpU67du3o378/M2fO9NXt3Lkzv/76KwBvv/02Rx99NJmZmfTu3Zv169db9s/NzeXyyy+nTZs2ZGRk0Lp1a+666y4KCwst9QYOHEiDBg3YvHkz/fr1o27dujRt2pR7770Xl8tlqZuXl8fAgQPJzs6mQYMGDBgwgLy8vIiukdvtpmHDhhaho6SkhKysLLKysigpKfGV33fffTRp0gStDVt/f3+2WbNmoZRi2rRpPP7447Rs2ZLMzEzOPvts1qxZE3DsiRMn0r59e7KysujWrRu5ubm2fdy5cyc33HADTZs2JTMzk86dO/Pxxx/H5BxC0aVLF+rWrWspa9y4Mb169WLFihW2+zzyyCMceeSRXHvttWEdww6lFHfeeSfvvfceHTt2pHbt2pxxxhmsXr0agNGjR9OmTRuysrLo168fe/fuDWjjiy++oEePHtSpU4fs7GwuvvjigN8hHuNSEARBMBg8eWGiuyAIFUYEOaHSWbp0Keeeey67du1ixIgRXH/99QwbNozp06db6o0YMYIbb7yR4447jueff57//Oc/fPrpp5x55pkBk9mVK1dy3XXX0b9/f5544gm2bNnCBRdcwBtvvMGTTz7J4MGDGTp0KPPmzePGG2+07PvRRx9RUFDAkCFDGDduHH379mXcuHFcd911AX0vLS3l3HPP5bDDDuPZZ5/ljDPOYMyYMUycONFXR2vNRRddxOTJk7n22msZOXIkW7ZsYcCAARFdp5SUFE477TSLEDV//nyKi4spLi5mwYIFvvLc3FxOP/30kMFiRo4cyWeffcb999/PAw88wNy5c7n66qstdd544w0GDx5MixYteOaZZzj99NPp168fmzdvttQrLCykT58+vPfeewwcOJBnnnmGjIwMLr/8cv73v//F7RxC8ddff9GkSZOA8qVLlzJhwgSee+65Ch8jJyeH//73v9xwww089NBDLFy4kIsvvpgnn3ySDz/8kHvvvZebb76ZL774gvvuu8+y71tvvUW/fv1o0qQJzzzzDA8++CC//vorPXv2tCxSxHpcCoIgCOXsLyxNdBcEoeJoreWvkv+AvOzsbO3Ehg0b9IYNGwLKS8tcetOe/KT5Ky1zOZ5DMPr3769r166tt2zZ4itbvny5Tk1N1caQ1Hr9+vU6NTVVP/vss5Z958yZo5VS+pVXXvGVtW3bVgN63rx5vrIpU6ZoQDds2FDv3r3bV/7ggw9qQG/atMlXVlBQENDHUaNGaaWU3rhxo69swIABGtBPPvmkpe4pp5yiu3Tp4vv+ySefaEA/99xzvrKysjLdq1cvDehJkyaFvEZennzySZ2Wlubr46hRo/Txxx+vjz32WP3UU09prbXOz8/XaWlpevTo0b79evfurXv37u37npOTowHdqVMnXVJS4it/4YUXNKCXLl2qtda6pKREH3bYYbpLly6WehMnTtSApc2xY8dqQH/wwQe+sqKiIn3SSSfpZs2a+faP9hyi4aefftJKKT18+PCAbX369NGXXnqp1toYX4B+/vnnIz4GoDMzMy1j6Omnn9aA7tChgy4qKvKV//Of/9QZGRm+a3Hw4EGdnZ2tb731Vkub69at01lZWXro0KG+sliPy8rC6fklCIKQTHQa9o1uO/QL358gJCPZ2dkayNMOMkWtyhYchejZvr+IXs84B3GobHLvP5PWjWpHtI/L5WLGjBlceumltGzZ0ld+7LHH0rdvX7766isApk+fjtaaSy65hN27d/vqHXXUUTRv3pxZs2Zx8803+8pPPPFEunXr5vvevXt3APr160fjxo0DytevX0/r1q0ByMrK8m3Pz8+nsLCQHj16oLVm8eLFtGnTxnIOgwcPtnzv1asXkydP9n3/6quvSE9Pt9RLTU3ltttuczRRdKJnz56UlpYyd+5czjzzTH7++Wd69eqF2+3m559/ZujQocydO5fS0lJ69uwZsr0bbriBtLQ0S98B1q1bR6dOnViwYAE7d+7kySeftNQbOHBggGbpq6++omXLllxxxRW+soyMDIYMGcLNN9/MwoULOfXUU2N+Dk7s3LmTf/3rX7Rv3557773Xsu3jjz/ml19+cTS5jJRzzz3XN36gfFz961//IiMjw1L+/vvvs337dtq0acPMmTPZv38/V1xxhWVc16tXj5NOOolZs2b5ymI9LgVBEIRyUlOqb7ojoeYgppVCpbJr1y4KCwvp0KFDwLZjjjnG93n16tW43W6OPPJImjZtavnbtm0bu3btsuzrP6nNzs4GsEy2zeX79u3zlW3atImBAwfSqFEjn39R7969Adi/f79l/7p169KoUSNLWcOGDS3tbdy4kZYtW1K7tlXINZ9fuHTr1o2MjAxyc3PRWjN79mx69epFz549mT17NlprcnNzycrKokuXLiHb879ODRs2BMqvx8aNGwECfp+0tDSOPPJIS9nGjRs5+uijA8wUO3bsaGkr1udgR35+PhdccAH5+fl8+umn1KlTx7etqKiIe++9lzvuuCPgHKIl2vHm9aM744wzAsb13LlzLeM61uNSEARBKCelGuetFWoOopFLAtxuzTtzNnBs8/p0P7KxY73m2Znk3n9mJfYsOM2zM+PWttvtJjU1la+//trWn8krgHhJTU21bcepXHsCarhcLs455xz27t3L0KFD6dixI3Xq1GHr1q0MHDgQt9saycqpvXiRkZFB165dyc3N5Y8//iAvL49evXrhcrnYt28fy5YtIzc3l+7du1s0aE6Euh7xINbn4E9JSQmXXHIJS5cu5dtvv+W4446zbH/55ZfZs2cPV199NRs2bABgy5YtgBHFcsOGDbRs2TKiY0c73rzj6b333qNp06YB9bxauGQfl4IgCFUdUcgJ1QER5JKA6Yu3Mvzz5QBseOofjvVqpaZEbMqYbDRt2pSsrCyfZsLMn3/+6fvcvn17XC4XHTp0oF27dnHrz9KlS1m1ahVvv/22JYjEzJkzo26zbdu25OTkUFBQYNHKmc8vEnr27Mn48ePJycmhbdu2Pq1Py5YtycnJYe7cudx1111R99e/72Bojs444wxfeWlpKevXr+ekk06y1F2+fDlaa4uw7T1Pb1vxPAe32811113H999/z8cff+wzFTWzadMmDh06xMknnxyw7fHHH+fxxx9nxYoVPk1iPGnfvj0AzZs3t0QV9Sce41IQBEEop6JBrwQhGRDTyiRg8eaaY/6UmppK3759mTZtGlu3bvWVr1ixghkzZvi+X3zxxaSkpPDYY48FtOF2u21DukfbH7BqpLTWvPDCC1G3ef7551NSUmJJqeByuRg3blxU7fXq1Yv8/Hxeeukli6DSq1cvxo8fT35+vq0AEw1du3aladOmvPrqq5SWlkf0euuttwLSJ5x//vls2bLFkm6gpKSEV155hWbNmlnMJON1DrfddhtTpkzh5Zdfpn///rZ1/v3vfzN9+nTLn/e3ueGGG5g+fTqtWrWK+NjRcO6551K/fn2efPJJysrKArZ7/ebiMS4FQRCEclJFkBOqAaKRSwJqpdQseXrEiBF88803nH766QwZMoSysjLGjRvH8ccfz++//w4YQU0ee+wxHn74YdauXcuFF15InTp1WLt2LVOnTuWhhx4KSCMQDR07dvQFx9i6dSv169dn6tSpFfItuvDCCzn99NO59957Wbt2LcceeyzTpk0L8GsKF29I/lWrVnHPPff4ynv27MkHH3xAamoqp512WtT9NZOWlsbIkSMZPHgwZ511FldccQXr169n0qRJAf5lgwYNYsKECVx77bXMnz+f1q1b8/7777NkyRImT55sMVWMxzmMHTuWl19+mdNOO43atWv7Uh54ueaaawA44YQTOOGEEyzbvCaWJ5xwgqMAGA+ys7MZP348AwYMoGvXrlx55ZU0btyYDRs28Nlnn9G/f39GjhwZl3EpCIIglCOmlUJ1QAQ5odI58cQTmTFjBnfffTePPvoorVq1YsSIEWzfvt0nyAE89NBDdOjQgbFjxzJs2DBSUlJo06YN/fv355xzzolJX9LS0vj888+5/fbbGTVqFJmZmVx88cXceuutFjPCSEhJSeGzzz7jzjvvZPLkySil6NevH2PGjOGUU06JuL0GDRrQqVMnli5daonq6NVgnXjiidSrVy+qvtoxaNAgXC4Xo0eP5r777uOEE07gs88+45FHHrHUy8rKIicnhwceeIA333yTgwcPctxxx/Hhhx9y+eWXx/0clixZAsCcOXOYM2dOwHavIJdsXHvttbRo0YKnnnqKp556itLSUlq1akWfPn246qqrgPiMS0EQBKGcFJHkhGqAimeQA8EepVRednZ2ttdUbfhny3jrlw2A4SPnjfZn9jESBEGoCsjzSxCEqkDv0Tls3FPg+x4sRoEgJIoGDRqwf//+/VrrBnbba5ZNnyAIgiAIglDjER85oTogppVJhmhIawYlJSUhA7ZkZ2dbkkLXFAoLC0P6EzZq1Ij09PSYHvevv/4Kuj0rK8uXF04QBEGo2phNK8XKUqiqiCCXZIgcVzP45ZdfOPPM4DkBJ02axMCBAyunQ0nElClTuP7664PWycnJCRq+PxqaN28edPuAAQN46623YnpMQRAEITGYhbdUkeSEKooIckmAWbsvclzN4KSTTgqZE+z444+vpN4kF3379g15beIR8CPUMVu0aBHzYwqCIAiJIcU0+RJBTqiqiCCXZIhpZc2gYcOG/O1vf0t0N5KS5s2bh9SOxQP5PQRBEGoOZkGupqWBEqoPMnKTDBHjBEEQBEEQ4otZCycaOaGqIoJcEqAof4CIQk4QBEEQBKHyEDlOqKqIIJdkaNHJCYIgCIIgxBW3rJwL1QAR5JIMea4IgiAIgiDEF5e7fMKlJKecUEURQS4JkOeHIAiCIAhC5VFc5vZ9zqgl02GhapLQkauUaq6UekoplaOUOqiU0kqpPiH2aauUKvDUPdlmewOl1ESl1C6lVL5S6ge7ep66/ZRSi5RSRUqpTUqpYUqpgEiekbRZUUQjJwiCIAiCEF/qZ6X5PtfNkCDuQtUk0UsQxwBDgVbA72Hu8yzgttuglEoBvgSuAsYB9wPNgFlKqfZ+dc8DPgH2Ard5Pj8KPB9tm4IgCIIgCELyc0rrBr7PbRvXSVxHBKECJFqQWwg00Vp3AEaHquzR1vUDxjpUuQzoAVyntX5Ma/0S0Acjqv8wv7rPAouBvlrr17TWtwOjgFuUUh2ibLPC1ORgJ8OHD6/WduobNmxAKcVbb70V92P16dOHPn36JH2bgiAIgpAIrNONmjv3Eqo2CRXktNYHtdZ7wqmrlEoFXgDGA2scql0GbAM+NR1jF/Ah0F8pleZp6zjgOGCC1tpl2v9ljGtyaaRtCoJQuRw6dIhhw4bx97//nUaNGoUUkouLi3n88cc5+uijycjIoHnz5lx88cXs27fPUm/hwoX84x//oFmzZtSrV49TTjmFV199Fbfb1hBAEARBqIKIK4tQHahKRsGDgZbA40B/hzqnAAu1Drg9fwUGAUcBKzz1ABaYK2mttymltpi2R9KmD6VUXohzyXbaIA8WIRZ8++23ie5C3Nm9ezePPfYYrVu35uSTTyYnJ8exbklJCeeddx6//fYbgwYNokOHDuzevZvZs2dTUFBAw4YNAVi0aBE9evTg6KOP5oEHHiArK4svvviCIUOGsHXrVh5//PHKOj1BEAShkpC5l1BVqRKCnFKqEYYAN0xrnRfE/K458INN+XbP/xYYQldzv3L/ui2iaDMmyLNEiAXp6emJ7kLcad68Odu2baN58+YsWbKEU045xbHumDFjWLx4MQsXLuTII490rPfaa68B8OOPP9KoUSMABg8eTLdu3XjnnXdEkBMEQagmBK7PC0LVI9E+cuHyGLATeDVEvSyg2Ka8yLTd/N+pbpbpe7ht+tBaNwj2B+wPcR7Vnp9//pn/+7//IzMzk/bt2zNhwgTbepMmTaJz585kZWXRpEkTBgwYwI4dOyx12rVrR//+/Zk5c6avbufOnfn1118BePvttzn66KPJzMykd+/erF+/3rJ/bm4ul19+OW3atCEjI4PWrVtz1113UVhYaKk3cOBAGjRowObNm+nXrx9169aladOm3HvvvbhcLkvdvLw8Bg4cSHZ2Ng0aNGDAgAHk5eVFdI3cbjcNGzbk/vvv95WVlJSQlZVFVlYWJSUlvvL77ruPJk2a+F5M/v5ss2bNQinFtGnTePzxx2nZsiWZmZmcffbZrFkTaKk8ceJE2rdvT1ZWFt26dSM3N9e2jzt37uSGG26gadOmZGZm0rlzZz7++OOYnEMovOaRoXC73YwbN45BgwZx5JFHUlJSQlFRkW3dAwcOkJmZSYMGDXxlSimaNWtGVlbArR6UPn36cPLJJ7No0SJ69uxJ7dq16dixI1999RUAX331FSeddBKZmZmccsopLFq0KKCNZcuWcckll9CoUSOysrI49dRTmTlzpqXOxo0bueWWWzjmmGPIysqicePGXH755WzYsMFS76233kIpxdy5c7nzzjtp2rQpderU4eKLL2bXrl0RnZsgCEJVRzt8FoSqRNJr5JRSnYCbgX5a67IQ1QuBDJvyTNN283+nuuYZfLhtxoSgk1hXGRzYGsvDVYz6LSE18iG0dOlSzj33XA477DBGjBhBaWkpw4YNo1mzZpZ6I0aM4LHHHuOf//wngwYNYvv27bzwwgvMnz+fhQsXWibWK1eu5LrrrmPIkCFcc801PPXUU1xwwQWMGjWKZ555hsGDB3PgwAGefvppbrzxRr7//nvfvh999BEFBQUMGTKExo0b8+uvvzJu3Di2bNnCRx99ZOlTaWkp5557LqeffjrPPvssM2fOZMyYMbRv354hQ4YAxm940UUX8fPPPzNkyBA6duzI9OnTGTBgQETXKSUlhdNOO80iRM2fP5/iYmNdYcGCBfTo0QMwhNHTTz89ZLCYkSNHkpqayv3338++ffsYPXo0V199NfPmzfPVeeONNxg8eDA9e/bkzjvvZN26dfTr149GjRrRunVrX73CwkL69OnDunXruO2222jdujXvv/8+l19+OZMnT+aaa66JyzlEyrJly9i+fTtHHXUUl112GZ988gkul4vu3bvz0ksv0aVLF1/d3r1789577zF48GDuueceMjMz+fzzz5kxYwYTJ06M+Nh79uyhX79+XHPNNVx55ZW8+OKLXHLJJUyaNIn77ruPW265hVq1ajFq1CiuuuoqVq5cSUqKsb62dOlSevbsSdu2bXnwwQfJzMzk3Xff5bzzzmPGjBmcffbZgHE9f/nlF6666ipatWrFhg0beOWVV+jTpw/Lly+ndu3alj7dcsstNG7cmOHDh7N+/XrGjh3LrbfeypQpUypwlQVBEKoWopATqgNJL8gBTwKLgOVKqXaesiae/y2UUnu01ps937dTbjZpxlu2zVTPW+5vXtkc+MX0Pdw2Y0LQ58qBrfDCibE8XMW443do2Dbi3R599FGUUsyePZuWLVsCcOmll3LCCSf46mzYsIHHH3+cZ555hnvuucdXft5559GjRw/efvttbr75Zl/5n3/+ybx58+jWrRsArVq14sorr+S+++5j9erVNG7cGDAEsVGjRrF582afUPL0009bhMJBgwZx1FFH8d///pdNmzbRpk0b37aCggKuu+46HnzwQQBuvvlmOnfuzBtvvOET5D777DN++uknnnvuOe666y4AhgwZwplnnhnxterVqxfDhg2jsLCQrKwscnNzOe6443C73eTm5tKjRw8KCgpYtGgRTz75ZMj2SktLmTdvHmlpRoyeRo0acccdd/DHH3/QqVMnSktL+e9//0uXLl344YcffPWOO+44Bg0aZBHkJk6cyIoVK/jggw+48sorAcMMsXv37tx7771ceeWVpKWlxfwcIsWrcXzwwQc58sgjefvtt8nPz+exxx7jrLPO4vfff6dtW2Mc//vf/2bp0qVMmDCB119/HYC0tDQmTpzI9ddfH/Gxt2zZwocffsjll18OQPfu3enevTsDBgxg6dKlHHPMMQA0aNCAwYMHM3v2bHr16gXAnXfeyVFHHcXcuXN9v8OQIUPo3LkzDz30kE+Q+8c//sFll11mOe6FF17IaaedxtSpU7n22mst2w477DC+/vprn8Dsdrt58cUX2b9/P9nZju67giAI1QpzlHAxsxSqKlXBtLIN8H/AetOfN1XBl8B8U90lQBcVuKTfHThEebTLJZ7/Xc2VlFItMHLaLTEVh9umEAYul4sZM2ZwySWX+IQ4gGOPPZa+ffv6vk+fPh2tNZdccgm7d+/2/R111FE0b96cWbNmWdo98cQTfUIcGBNmgH79+vmEOHO52bzSLMTl5+eze/duevTogdaaxYsXB5zD4MGDLd979erFunXrfN+/+uor0tPTLfVSU1O57bbbgl8cG3r27ElpaSlz584FDJPUXr160atXL37++WcA5s6dS2lpKT179gzZ3g033OATCrx9B3z9X7BgATt37mTIkCGWel4zUTNfffUVLVu25IorrvCVZWRkMGTIEHbs2MHChQvjcg6RcujQIcAwkfzhhx+4+uqrGTRoEN988w0HDx5k7Nixvrqpqam0b9+ev//977z99ttMmTKFf/zjHwwePJjPP/884mM3aNDAImR17dqV1NRUevTo4RPiIHBc7t27l5ycHC6//HL279/vG/95eXmce+65zJ8/n4KCAsA6fktLS9mzZw9HHXUUDRo0sDXXHDx4sEXr2atXL1wuFxs3boz4/ARBEKoDIsYJVZWqoJG7i8Aoj2dhJPG+G2ugkY8x0gVchJHgG6VUE+By4FOtdSmA1nqZUmolMEgp9YYpBcEQjGTjUyNtM1YEXRSq39LQgiUL9VuGruPHrl27KCwspEOHDgHbjjnmGJ//0OrVq3G73Y6BKfx9esxaM8AndJg1SOZyc8j5TZs28eijj/LZZ58FhKLfv9/qzli3bl1fEAwvDRs2tOy3ceNGWrZsGWDSZp64h0u3bt3IyMggNzeXPn36MHv2bF566SVcLhd33HEHWmtyc3PJysqymAg64X+dvNEavf33Tub9f5+0tLSA32Ljxo0cffTRAaaQHTt29G0/9dRTY34OkeIVdC688ELq1q3rK+/UqRMnnXQSs2fP9pU9/fTTjBs3jlWrVvl+vyuuuIIzzzyT//znP5x//vmkpqaGfexWrVpZrk9KSgp169YNOS7XrFmD1poHH3zQp/31Z8+ePdSuXZvCwkJGjRrFpEmT2Lp1q2Vl2X/8QugxIAiCUBMQJZxQHUi4IKeUetjz8VjP/2uVUj2BPK31eK11QExxpVQDz8ccrfUS06aPgbnAO0qpZ4HdwC0Ymsfhfs3cB3wGzFBKTQE6Abdi5JZbFWWbURH2wyS1VlSmjFURt9tNamqqxQTMjHfy6cVpcu1U7p3sulwuzjnnHPbu3cvQoUPp2LEjderUYevWrQwcODAgd1gkk/hYkJGRQdeuXcnNzeWPP/4gLy/Pp0HZt28fy5YtIzc3l+7du1s0aE6Euh7xINbnECnegCj+PpjesrVr1/q+v/TSS5x99tkBQni/fv24++672bx5M+3atQv72NGOS++4Gzp0KH/7299s6zZt2hSA2267jUmTJnHnnXdy2mmnkZ2djVKKq666yjb3XSLGgCAIQrJhCXYijz+hipJwQQ4jrYCZGzz/N2Ik/w4brbVLKXU+hunl7RgRJX8FrtNar/Gr+4VS6hJgGDAO2AWM9O9PJG3GhGr+MGnatClZWVmsXr06YNuff/7p+9y+fXtcLhcdOnSIaOIcKUuXLmXVqlW8/fbbXHfddb5y/8iAkdC2bVtycnIoKCiwCATm84uEnj17Mn78eHJycmjbtq1Pm9OyZUtycnKYO3euzxevonh9xVavXs0ZZ5zhKy8tLWX9+vWcdNJJlrrLly9Ha20Rtr3n6W2rss/BnxNOOIG0tDS2bg0MFLRlyxafQASwY8eOgAikYJw/QFlZqHhLscGr/czMzHQU5Lx8/PHHDBgwgDFjxvjKioqKIo6SKgiCUJMQ4U2oDiTcR05rrRz+2gXZ5y1PnSU22/ZprW/UWjfRWtfRWp+ptQ50FDHqfqK1PkVrnam1bq21HmYXGTOSNqPBrHDS1VySS01NpW/fvkybNs0ysV6xYgUzZszwfb/44otJSUnhscceC2jD7Xazd+/emPUHrNoIrTUvvPBC1G2ef/75lJSUWFIquFwuxo0bF1V7vXr1Ij8/n5deesnn0+YtHz9+PPn5+ZbyitC1a1eaNm3Kq6++6hNewAhd7y8YnH/++WzZssWSbqCkpIRXXnmFZs2aWcwkK/Mc/Klfvz59+/bl008/Zffu3b7yOXPmsGzZMougdPTRRzNjxgyLmaHL5eLDDz+kQYMGHHHEEXHpoz+HHXYYZ5xxBq+88optagBzWWpqaoA2bdy4cbYCqSAIguBF23wShKpFMmjkajw1bVVoxIgRfPPNN5x++ukMGTKEsrIyxo0bx/HHH8/vvxs+gEcddRSPPfYYDz/8MGvXruXCCy+kTp06rF27lqlTp/LQQw9x4403VrgvHTt2pH379tx7771s3bqV+vXrM3Xq1Ar5C1144YWcfvrp3Hvvvaxdu5Zjjz2WadOm2forhYM3JP+qVassETx79uzJBx98QGpqKqeddlrU/TWTlpbGyJEjGTx4MGeddRZXXHEF69evZ9KkSQE+coMGDWLChAlce+21zJ8/35d+YMmSJUyePNliJhmvcxg/fjx5eXn89ddfAHz++eds2bIFgIcffthXb9SoUXTv3p0ePXpw8803k5+fz/PPP0/r1q258847ffUeeOABrrnmGrp168agQYPIzMzk/fffZ+HChTz11FOValrrFXo7derEjTfeyBFHHMH27dvJzc2lqKiIn376CYALLriAyZMnk52dzXHHHcecOXP47rvvLEF+BEEQBCs1be4lVE9EkEsyasKD5cQTT2TGjBncfffdPProo7Rq1YoRI0awfft2nyAH8NBDD9GhQwfGjh3LsGHDSElJoU2bNvTv359zzjknJn1JS0vj888/5/bbb2fUqFFkZmZy8cUXc+utt1rMCCMhJSWFzz77jDvvvJPJkyejlKJfv36MGTOGU045JeL2GjRoQKdOnXx5xbx4NVgnnngi9erVi6qvdgwaNAiXy8Xo0aO57777OOGEE/jss8945JFHLPWysrLIycnhgQce4M033+TgwYMcd9xxlnD78T6HZ5991hJtcdq0aUybNg2wCnKdOnVi1qxZ3H///TzyyCPUqlWLc889l2effdYSvObqq6+mSZMmvvyDBw4coGPHjkycOJGbbrop4v5VhE6dOjF//nyGDx/O66+/Tl5enk/Teccdd/jqvfDCC6SmpvLuu+9SVFTE6aefznfffWeJAisIgiBYMc+3xEdYqKooGbyVj1IqLzs7O9trqvb4F8t542cj7PiiR87h4G4jtZ3Zx0gQBKEq4BWs5fklCEIyc//Hv/HhAsOCo1eHJkz+d/cE90gQAmnQoAH79+/fr7VuYLc94T5yQs3QwgmCIAiCICQLMvcSqgNiWplkiIa0ZlBSUhIyYEt2drYl2XNNobCwMKQ/YaNGjUhPT6+kHlnZu3cvJSUljttTU1MtkTAFQRCE5EPSDwjVARHkkgBr1EqhJvDLL79w5plnBq0zadIkBg4cWDkdSiKmTJnC9ddfH7ROTk4Offr0qZwO+XHJJZfw448/Om5v27YtGzZsqLwOCYIgCBEjwptQHRBBThASwEknnRQyV93xxx9fSb1JLvr27Rvy2kQbiCYWjBkzJmhU05qoRRUEQajKVPfUT0L1RQS5JENWiGoGDRs2DJnouabSvHlzmjdvnuhuOGLOjycIgiBUTUR4E6oDEuwkCRDhTRAEQRAEoRKxpB9IXDcEoSKIIJdkyAqRIAiCIAhCfJFgJ0J1QAS5JMAc7ETkOEEQBEEQhPgiUcKF6oAIckmAPEsEQRAEQRAqD4tGTlbRhSqKCHJJhjxKBEEQBEEQ4ossogvVARHkkgBLHjl5sAiCIAiCIMQV8ZETqgMiyCUB8gAxGD58OMriMFi92LBhA0op3nrrrbgfq0+fPjFPmB2PNgVBEAQhEZh95GQaJlRVRJBLMsROWxDCZ/v27dx00020a9eO2rVr06FDBx544AHy8vIs9ZRSjn/nnHNOQLurVq3iyiuvpGnTpmRlZXHsscfyzDPPBNT75Zdf6NmzJ7Vr1+bwww/njjvuoKCgIF6nKwiCIMQImW0J1QFJCC4I1ZBvv/020V2IO/n5+fTo0YNDhw7xn//8h1atWrF48WLGjBnD7Nmzyc3N9dWdPHlywP4LFizghRde4Nxzz7WUL1q0iDPPPJOOHTvy4IMPUq9ePdatW8fmzZst9ZYsWcLZZ5/N8ccfz3PPPceWLVt49tlnWbduHZ9//nl8TloQBEGIPSLVCVUUEeSSDDGzFGJBenp6orsQd7744gs2bNjAF198wT/+8Q9feVZWFmPGjGH9+vUcccQRAFxzzTUB+8+aNQulFP/85z99ZS6Xi2uvvZazzz6bjz/+mJQUZ6OF//73vzRu3JhZs2ZRt25dANq1a8dNN93EDz/8wFlnnRWrUxUEQRBijcy3hGqAmFYmGTXlufLzzz/zf//3f2RmZtK+fXsmTJhgW2/SpEl07tyZrKwsmjRpwoABA9ixY4elTrt27ejfvz8zZ8701e3cuTO//vorAG+//TZHH300mZmZ9O7dm/Xr11v2z83N5fLLL6dNmzZkZGTQunVr7rrrLgoLCy31Bg4cSIMGDdi8eTP9+vWjbt26NG3alHvvvReXy2Wpm5eXx8CBA8nOzqZBgwYMGDAgwNwvFG63m4YNG3L//ff7ykpKSsjKyiIrK4uSkhJf+X333UeTJk18Nv/+/mxeoWXatGk8/vjjtGzZkszMTM4++2zWrFkTcOyJEyfSvn17srKy6Natm0W7ZWbnzp3ccMMNNG3alMzMTDp37szHH38ck3MIxYEDBwBo1qyZpfzwww8HDIHOieLiYqZOnUrv3r1p1aqVr/zbb79l+fLlPPHEE6SkpHDo0CHcbrftsWfOnMl1113nE+IA3/cPP/wwrHOAct/JsWPHMnbsWNq1a0edOnW44IIL2LVrF2VlZQwdOpRmzZpRt25dBg4cSFFRUUA74dwrn376Kf/4xz9o0aIFGRkZtG/fnscffzxg/Pbp04eTTz6ZP/74gz59+lC7dm1atmxpa14qCIJQFTG7sohbi1BVEUFOqHSWLl3Kueeey65duxgxYgTXX389w4YNY/r06ZZ6I0aM4MYbb+S4447j+eef5z//+Q+ffvopZ555ZoCQtXLlSq677jr69+/PE088wZYtW7jgggt44403ePLJJxk8eDBDhw5l3rx53HjjjZZ9P/roIwoKChgyZAjjxo2jb9++jBs3juuuuy6g76WlpZx77rkcdthhPPvss5xxxhmMGTOGiRMn+uporbnooouYPHky1157LSNHjmTLli0MGDAgouuUkpLCaaedZhGi5s+fT3FxMcXFxSxYsMBXnpuby+mnnx4yWMzIkSP57LPPuP/++3nggQeYO3cuV199taXOG2+8weDBg2nRogXPPPMMp59+Ov369QswLSwsLKRPnz689957DBw4kGeeeYaMjAwuv/xy/ve//8XtHLz06tWLlJQU7rjjDubOncuWLVv4/PPPGTNmDAMHDvQJdHZ89dVX5OXlBZz7d999R/369dm6dSvHHHMM9erVo169etx0000W37elS5dSVlZG165dLfunp6dz8skns3jx4rDOwcxbb73FG2+8wZ133sltt93GN998w8CBA7n11ltZtGgRjz76KJdddhlvv/02o0ePtuwb7r3y1ltvUbduXe6++25eeOEFunTpwqOPPsoDDzwQ0J89e/bw97//nVNOOYUxY8ZwzDHHMHToUL7++uuIz00QBCHZEAsooVqgtZa/Sv4D8rKzs7WXEZ8t022HfqHbDv1Cb96brzds2KA3bNig/Sl1leotB7ckzV+pqzSgj+HQv39/Xbt2bb1lyxZf2fLly3Vqaqo2hqTW69ev16mpqfrZZ5+17DtnzhytlNKvvPKKr6xt27Ya0PPmzfOVTZkyRQO6YcOGevfu3b7yBx98UAN606ZNvrKCgoKAPo4aNUorpfTGjRt9ZQMGDNCAfvLJJy11TznlFN2lSxff908++UQD+rnnnvOVlZWV6V69emlAT5o0KeQ18vLkk0/qtLQ0Xx9HjRqljz/+eH3sscfqp556SmutdX5+vk5LS9OjR4/27de7d2/du3dv3/ecnBwN6E6dOumSkhJf+QsvvKABvXTpUq211iUlJfqwww7TXbp0sdSbOHGiBixtjh07VgP6gw8+8JUVFRXpk046STdr1sy3f7TnEA6vv/66btCggcZQZmtADxo0SLtcrqD7XXrppTojI0Pv27fPUt6vXz9du3ZtXbt2bX3rrbfqqVOn6nvuuUcrpfRFF13kq/fRRx9pQP/yyy8BbV9++eW6VatWYZ/D+vXrNaAPP/xwfeDAAV/5kCFDfNfc7Xb7yk877TR95JFHWvYP916xG+uDBw/WtWvX1kVFRb6y3r17a0C/9957vrLi4mJ9+OGH60svvTTo+Tg9vwRBEJKJwe8s8M29Ln15dqK7Iwi2ZGdnayBPO8gU4iOXZARbIdpRsIO/T/175XUmBN9c+g0t67aMaB+Xy8WMGTO49NJLadmyfN9jjz2Wvn378tVXXwEwffp0tNZccskl7N6921fvqKOOonnz5syaNYubb77ZV37iiSfSrVs33/fu3bsD0K9fPxo3bhxQvn79elq3bg1YTfDy8/MpLCykR48eaK1ZvHgxbdq0sZzD4MGDLd979eplCabx1VdfkZ6ebqmXmprKbbfd5mii6ETPnj0pLS1l7ty5nHnmmfz888/06tULt9vNzz//zNChQ5k7dy6lpaX07NkzZHs33HADaWlplr4DrFu3jk6dOrFgwQJ27tzJk08+aak3cOBA7rvvPktbX331FS1btuSKK67wlWVkZDBkyBBuvvlmFi5cyKmnnhrzczDTqlUrTj31VM477zzatGlDbm4uL774Io0aNWLUqFG2+xw4cIAvv/yS888/nwYNGli2HTp0iIKCAm6++WbGjRsHwCWXXEJKSgqjR4/mt99+46STTvJpuTIyMgLaz8zMDNAYh8MVV1xBvXr1fN+7d+/OK6+8wsCBAy1ayu7duzN+/HjcbjcpKSkR3SvmsX7w4EGKi4vp1asXEyZMYOXKlZx00km+7dnZ2Vx11VW+7+np6XTr1o1169ZFfG6CIAjJhtW0UhCqJmJaKVQqu3btorCwkA4dOgRsO+aYY3yfV69ejdvt5sgjj6Rp06aWv23btrFr1y7Lvv7CVnZ2NoBPWPMv37dvn69s06ZNDBw4kEaNGvn83nr37g3A/v37LfvXrVuXRo0aWcoaNmxoaW/jxo20bNmS2rVrO55fuHTr1o2MjAxyc3PRWjN79mx69epFz549mT17NlprcnNzycrKokuXLiHb879ODRs2BMqvx8aNGwECfp+0tDSOPPJIS9nGjRs5+uijA0whO3bsaGkr1ufgZfbs2VxwwQWMGjWK22+/nf79+zNmzBgefvhhnn76af7880/b/aZOnUpRUVGAWSWUCzrmACiAr+7s2bMt9YqLiwPaKCoqCuqf50QkY7isrIyDBw8Ckd0ry5Yt4+KLLyY7O5v69evTtGlTXyAY/7HeunXrgN/Wf6wLQlVGa830xVtYuHFvorsiJAAxrRSqA6KRq0I0q92Mby79JtHd8NGsdrPQlaLE7XaTmprK119/besz5RVAvKSmptq241SuPU9wl8vFOeecw969exk6dCgdO3akTp06bN26lYEDBwYEunBqL15kZGTQtWtXcnNz+eOPP8jLy6NXr164XC727dvHsmXLyM3NpXv37hYNmhOhrkc8iPU5eJkwYQItWrTg5JNPtpT369eP4cOHM2fOHFvh+d133yU7O5sLLrggYFvz5s2BwAAq3u9eIcZbb/v27QFtbN++nRYtWoR9Hl6iHcPh3it5eXn07t2b+vXr89hjj9G+fXsyMzNZtGgRQ4cODXusx3OsCEJlkvPnTu6a8hsAG576R4jaQnXD/CST55pQVRFBrgpRK6VWxKaMyYY3wfLq1asDtpk1KO3bt8flctGhQwfatWsXt/4sXbqUVatW8fbbb1uCm8ycOTPqNtu2bUtOTg4FBQUWrZyThigUPXv2ZPz48eTk5NC2bVufhqZly5bk5OQwd+5c7rrrrqj76993MLQ8Z5xxhq+8tLSU9evXW0zv2rZty/Lly9FaWwQI73l624rXOezYsSMg2qK3rwBlZWUB27Zv305OTg4DBw60NYvs0qULr7/+ui/YiZctW7YAxvgF6NSpE7Vq1WLBggVccsklvnolJSUsWbKEf/3rXxGdS0UI916ZNWsWe/bsYdq0aZbf1j+KqyDUFOatF01cTUZkN6E6IKaVSUZ1f7CkpqbSt29fpk2bxtatW33lK1asYMaMGb7vF198MSkpKTz22GMBbbjdbvbujc0L2Kt1MK/Gaa154YUXom7z/PPPp6SkxJJSweVy+XyuIqVXr17k5+fz0ksv+XzavOXjx48nPz/fUl4RunbtStOmTXn11Vd9AhEY0Q790yecf/75bNmyxZJuoKSkhFdeeYVmzZpZzCTjcQ5HH300W7duDfA7fP/99wE45ZRTAvb54IMPcLvdtmaVYGjz0tPTeeONNyzlr732GkopX2647Oxs/va3vzF58mQOHTrkq+f9fvnll0d0LhUh3HvFbqyXlJTw8ssvV05HBSGJcbur+ctXsEF85ISqj2jkkoyakMtkxIgRfPPNN5x++ukMGTKEsrIyxo0bx/HHH8/vv/8OGIEaHnvsMR5++GHWrl3LhRdeSJ06dVi7di1Tp07loYceCkgjEA0dO3akffv23HvvvWzdupX69eszderUCvkBXXjhhZx++unce++9rF27lmOPPZZp06YF+CCFizck/6pVq7jnnnt85T179uSDDz4gNTWV0047Ler+mklLS2PkyJEMHjyYs846iyuuuIL169czadKkAB+5QYMGMWHCBK699lrmz59P69atef/991myZAmTJ0+2mEnG4xxuvfVWJk2axAUXXMCtt95KmzZt+PHHH3n//ff5+9//butv9+6779KiRQtLjj0zLVq04IEHHuCxxx6jpKSEs846i19++YX//e9/3HLLLRx11FG+uk888QQ9evSgT58+3HjjjWzZsoUxY8Zw3nnn8be//S2ic6kI4d4rPXr0oGHDhgwYMIDbb78dpRSTJ08WkyKh5mIa+m6tSSG81CdC9UAefUJ1QAQ5odI58cQTmTFjBnfffTePPvoorVq1YsSIEWzfvt0nyAE89NBDdOjQgbFjxzJs2DBSUlJo06YN/fv355xzzolJX9LS0vj888+5/fbbGTVqFJmZmVx88cXceuutFjPCSEhJSeGzzz7jzjvvZPLkySil6NevH2PGjLHVEoWiQYMGdOrUiaVLl1qiOno1WCeeeKIl2mFFGTRoEC6Xi9GjR3Pfffdxwgkn8Nlnn/HII49Y6mVlZZGTk8MDDzzAm2++ycGDBznuuOP48MMPAzRS8TiHY445hoULF/Lwww8zefJk/vrrL1q0aMH999/P8OHDA+r/+eefLFy4kLvvvpuUFGdjhOHDh9OgQQNefvllPv30U1q2bMnIkSN58MEHLfU6d+7Md999x9ChQ7nrrruoX78+N910k2O0zHgSzr3SuHFjvvjiC+655x4efvhhGjZsyDXXXMPZZ59N3759K73PgpBoXCYtnCjkajYi1AlVFSWrsZWPUiovOzs722uq9tjny3lztuGnMuvePqh8I4S42cdIEAShKuCNVirPLyHZGfH5MibN3gDAnyP/Tkatyg1mJSSWG96azw8rdwJwUusGfPqf0xPcI0EIpEGDBuzfv3+/1rqB3faE+sgppZorpZ5SSuUopQ4qpbRSqo9fHaWUmqCU+l0plaeUOqSU+k0pdbtSKiDEnVKqgVJqolJql1IqXyn1g1LqZIfj91NKLVJKFSmlNimlhimlArSUkbRZUUSsFgRBEIT4I+vYNRtRZAjVgUSbVh4DDAXWAL8DPWzqpACdgW+B9UAZcBowFugK+EINKqVSgC+BE4BngT3ALcAspVQXrfVaU93zgE+AH4DbPPs8CjTxfI+4TUEIl5KSkpABW7Kzs6PKR1bVKSwsDOlP2KhRI9LT0yupR9HhcrkC8h36U7duXerWrVtJPRIEwYw1yFUCOyIkBMtPLgNAqKIkWpBbCDTRWu9RSvUHpvtX0Fq7gP/zK56glDoA3KqUukdr7Z0tXYYhDF6stf4EQCn1IbAKGIZJ6MMQyhYDfT3HwNPmg0qpF7XWq6Nos8LIClHN4JdffuHMM88MWmfSpEkMHDiwcjqUREyZMoXrr78+aJ2cnBzHgCXJwubNmzniiCOC1hk2bJitP58gCPFH3rY1G5luCdWBhApyWuuDFdh9I6CAbMAsyG0DPjUdY5dH8PqnUipNa12qlDoOOA4Y7BXiPLwMPARcCjwVSZsVOA8L8lypGZx00kkhc9Udf/zxldSb5KJv374hr020gWgqk8MPPzzkefhHAhUEofKQiXzNRjt8FoSqRKI1cmHj8YfLBrIwTCrvBdZhmFt6OQVYqAPVWr8Cg4CjgBWeegALzJW01tuUUltM2yNpUxDCpmHDhpUaor4q0bx5c5o3b57oblSYzMxM+Y0FIYmpCel+BGfEAkqoDlSlhOB9MTRvm4BpwBbgIj+NWnNgu82+3rIWpnoEqdvC9D3cNn14grI4/mEIpLbIc0UQBEEQ4o/5fSvv3pqN/P5CVaXKaOSAucA5GELQWcDJgH+UgCyg2GbfItN283+nurWjaDNmKKVwuVyhKwpCDCgqdbEnv4SmddNJl/DbQgVxuVyWZPCCUBUQ7VzNwyLIy+8vVFGqjEZOa71ba/2d1nqq1vo/GD5rM5VSh5uqFQIZNrtnmrab/zvVLTR9D7dNc18bBPsDgoTk02RkZFBcXCzCnFAprNpxkD2Hilm/uyDRXRGqOG63m9LSUmrVqkprhEJNRabuNRsn4e2TxVu56Z0F7D5kt4YvCMlFlRHkbPgYQyN3kalsO+Vmk2a8ZdtM9QhSd5vpe7htxgStoX79+mit2b59uwhzQqVRXCZjTYgerTW7d+/G7XaTne1oPS4ISYOYVtZsnH7/O6csYebyHYz8Ynnld0oQIqQqL5t6TRrNM4YlQA+llPILTtIdOISRr85bD4ygKYu8lZRSLYBWpu2RtBkzsrKyaNasGTt27ODQoUNkZGSQklKVZW4hmSnLL1913LgxeP42QXCirKyMkpIS6tevT+3atUPvIAgJR6Q3wZkt+wIMrgQh6Uh66UAp1UgpZee4c6Pn/0JT2ccYwUd8WjqlVBPgcuBTb5oArfUyYCUwyK/tIYAbmBppm7HC+1pp1KgR7dq1o1GjRqSmit+SED++XbbD9ycI0ZKens7hhx9eLSKOCjUDq4+UUNMIpZGtlaoqrzOCECUJ18gppR72fDzW8/9apVRPIE9rPR7oBzyslJoGrAXqAOdiRLH8Umv9vam5jzGCoryjlHoW2A3cgiGwDvc79H3AZ8AMpdQUoBNwKzBBa70qyjYrjPlhkpWVRVZWzGOpCIKFV1/5w/f5gcvbJrAngiAIlYeYU9ZsQgU4UYggJyQ/CRfkgMf9vt/g+b8RGI+R6+1XDA3Y4Rgasz8x8si9aN5Ra+1SSp0PjAZuxzC//BW4Tmu9xq/uF0qpS4BhwDiM1AYj/fsTSZuCIAiCIFQ9JKdYzUM0skJ1IOGCnNY66JKH1voP4F8RtLcPw+zyxjDqfgJ8Ess2K0o4IXCLy1yM+XYV3do14m/HNYt3lwRBEASh2mF+38pEvuZh/s1FkBeqKgkX5ITw2bSngNlrd7Mtr5CJP61j4k/r2PDUPxLdLUEQBEGocsjcvYYjv79QDRBBLskI9mLp82wObnnwCIIgCEJMEaGu5iFJwIXqQNJHraxpBHuZiBAnCIIgJDt/bN3Ph/M340ryl1Zy906INyK8C9UB0cgJgiAIghAzLhj3MwBurbmqW5sE98YZy0ReJvU1DquPXMK6IQgVQjRySUakqn53kq94CoIgCDWTn1bvSnQXgiKmdTUbCXAiVAdEkEsyIn2ulLrd8emIIAiCIFRnLOHnZVJfk5HfX6iqiCBXxRE5ThAEQUhGkj2hskzdazZiWilUB0SQq+K45ekjCIIgCBFjNq2TV2nNQ35zoTogglySEemDRQQ5QRAEIRlRya2QsyBv0pqHxLoRqgMiyFVxJNaJIAiCkIykJLkkJ6/PGo4shAvVABHkkoxIHW4l6pIgCIKQjKQktxxnmcfLu7TmYfWRC/z9JQCKUBVwzCOnlHoziva01vrfFehPjaQiDwvRyAmCIAjJgnlCnEiN3J5Dxdz70W/0Pf5wx1x28vqs2YSS3UW2F6oCwRKCD7Qp8w5r/6ez9pRpQAS5ChDpg8MlkpwgCIKQJFjeYVHKcW63JqWC6rwnvlxBzp+7yPlzV1hJyeVNWvMwL6Lb/f5KGXOs1GRXLQs1GkfTSq11ivkPaAYsAT4FegANPH+nA58Bizx1hAgxh2iO9GUi5iCCIAhCslCRN1KZy03/l2bzt+d/pLjMVaF+bNxbELKOvD9rNjpEtJO56/ZywvAZfL10e6X1SRAiJRIfueeAnVrrS7TWc7XWBzx/c7TWFwO7PXWECBHTSkEQBKE6UBHhaO2ufJZszmPdrnzmr98X935IHrGajd1v7j9uCkpcDHl3USX1SBAiJxJB7nzg8yDbP/fUESqA08vHqVzSDwiCIAjJQkXeSOb32cGi0krthwS2qHnYKeRkSiVUNSIR5DKAVkG2t/LUESIkHNNKJ184EeQEQRCEZKEir6RKj40ir0/BDxkSQlUjEkHuZ+A2pdQZ/huUUr2B24DZseqYYMXlqKmr5I4IgiAIggNmzZaKNtoJFZ9Qh/NutGjh5F1a4zBbOnk/i9+kUNUIFrXSn7sxhLkcpdQCYKWnvCPQFTgA3BPb7tU8nJ4hopETBEEQkp0KaeTM1imV8GqT16fgjwwJoaoRtkZOa70c6AxMAY4FrvX8Hesp66K1XhaPTlZ3wrHNdxbkYt0bQRAEQah8zKaVltDwWrNpT0HMtSVaFHI1GrvfX4R7oaoRiWklWusNWut/AdlAc89fA631v7TW6+LRwZqHg8Dmtq8teeQEQRCEZKFiGjn7dl6etZYzRucw8ssV4fcjrDry/qzJWBcLAssEoSoQkSDnRRvs8Pw5iBhCuIRjTlLmIMmJPbcgCIKQLFRkImzVyJUzesafALzx8/qo2w6FvEprHvbpByq/H4JQESLxkQNAKdUB6AA0hkBPZq31OzHoV40iLNNKx/QDse6NIAiCIESH+Z0UaRRK82uuwgEsw8kjJ+/PGo01/UDwwfDyrDXcfEZ7UlIqO7SqIAQnbEFOKdUMeBs4x1tkU00DIshVAEk/IAiCIFRVzFYiFZnyVkYqgkgm8kL1w86iyWlK9cw3f9KkbgZXdG0d514JQmREopEbjyHEvQL8AOyJS49qIOGYVoogJwhCslJQUsaD05bSo31jrvy/NonujpBAKvJGSuTbTF6lNQ+LIB+Gj9zSLftFkBOSjkgEuXOAV7XWt8arMzWVcFYCnYKdyMtHEIRE88qstXy6ZBufLtkmglwNJ1bvpIrkoIMwg53I+7NmE+HvLwvnQjISSbCTFOC3eHVEMHAKXuIU7EQeLIIgJJr1u/MT3QUhWahSryRt80moKdhq5IIMBJlvCclIJIJcLnBSvDoiBMfpASLpBwRBSDQywRG8VMTXrLKHkQxbwR8ZEkJVIxJB7m7gYqXUpfHqjOD8ECmThOCCICQpZS55EAkGlsiTFbCOrGiwk3CENKtGRsZwTcM+2ImMA6FqEYmP3CvAIeBDpdQ2YB3g8qujtdZnx6pzNZFIg53IQ0cQhEQjlgGCl4oFO6mccVRU6mLUVyv4YeXOSjmekJzYCfLyJBOqGpFo5I4E0oBNQBnQBjjC7+/ISA6ulGqulHpKKZWjlDqolNJKqT5+dRorpe5TSuUqpXYppfKUUnOUUpc7tNlAKTXRUzdfKfWDUupkh7r9lFKLlFJFSqlNSqlhSqkA4TaSNuOFU7ATmT8JgpBoSuVBJHiI1eJiPLMPTPxpHW/P2WgpkzXRmockBBeqA2Fr5LTW7eJw/GOAocAa4Hegh02d04AngK+AkRhC5KUYmsFHtdaPeysqpVKAL4ETgGcxUiTcAsxSSnXRWq811T0P+AQjlcJtnn0eBZp4vkfcZrSYHxxOK5IS7EQQhGTF5bTSJNQ4KqSRi5FZptEP5578un5vxRoXkpo9h4ppUDud1BDJu7VdsBuZUglVjEg0cvFgIdBEa90BGO1QZxnQQWvdX2v9gtb6JeBsDAHsQaVUlqnuZRjC4HVa68c8dftg3JrD/Np9FlgM9NVav6a1vh0YBdyilOoQZZsVx+Eh4iSwiSAnCEKiMfvIrdpxkJ5P/8DEnyq8xiVUQSrySrLuGz+dXH5JWdzaFhLLks15dBn5HTe8NT9kXcsiehh55OKrJxaE6EioIKe1Pqi1DppYXGu9Xmu90a9MY2jTsoB2pk2XAduAT011dwEfAv2VUmkASqnjgOOACVprs5/fyxjXxBzQJaw2441TMAGR4wRBSDTmx9AdHyxhy75CnvxqZcL6IyQO80Q40lxwleUj57YxBZZ3afXgya9WAPDjql0h64pppVAdiCTYCUqp9sBdQHegIYGCoNZat49R30JxuOf/blPZKcBCHWik/yswCDgKWOGpB7DAXElrvU0ptcW0PZI2fSil8kL0Pdtpg9MzxCUaOUEQqgA7DxQlugtCIolVQvA4Rq0sLhNT4OpKqSu639a7iCAzKqGqEbZGTil1ArAIuBFIxwhskg9kYmjFXBiBUOKOUqqRpx+zPNoxL82B7Ta7eMtamOoRpG4L0/dw24was4zo9PJxckGRsN+CICQa85xbJsk1m1j5yMUTuzFaWdpAIb5EEkHXO/e6NOUn5pVcCutzJRK4UOWIxLTyMaAEIym4N8XAHVrrFsBgoAHwn5j2zgZP8JF3MbRat/ttzgKKbXYrMm03/3eqa/a7C7dNH1rrBsH+gP2W+jaN++MU7CTa1SdBEIR4IM+kmk2srETi6Y3k9D4Vqj6RDD+vDm5M+qtGwdsXBJ2PLd2aF3W/BCFeRCLI9QQmaq3/pFz2UABa69eAr4GnYts9W8YBfYHrtdZL/bYVAhk2+2Satpv/O9UtNH0Pt82Y4LQq6PRyLBWNnCAISUSZpCKo0VQk8mRlKUOOalo3YccWkotGHLR8DzYO/th6gEPFEihHSC4iEeTqAd4wZCWe/3VM22djCHtxQyk1DCP0//1a6/dtqmyn3GzSjLdsm6keQepuM30Pt82oCecF4lRHVr8FQUgmJDl4zSZWCcFVRZ3kgnB4dmZAmYzamofW0FyZUlHUbhLSxHZffknQ7YJQ2UQiyO3AE2BEa30Qwz/uaNP2hkBq7LpmRSn1H2A48LzW+lmHakuALirwDdAdOISRr85bD6Cr3zFaAK1M2yNpM2osuUwcniFO5SXVXJDbcaCIolJX6IqCIAhCwjH7GCVSIxesLVlsEMCYezUzC3JptRPXGaFasPNAUaVrbSMR5JZgFXx+BO5QSp2hlOoD3Ar8FrOemVBKXQm8iOEbd0+Qqh9jBB+5yLRvE+By4FOtdSmA1noZsBIYpJQyC59DADcwNdI2Y4XT68XJtLI6O+au2XmI7k9+z2Wv/pLorlRbqvP4EQSh8qlQHjnT53j6yNmtf8qzsOYRoJErKxTVrBA1W/MK6fbk93R74jvbFCfxIpL0A+8B/1FKZWmtC4FHMIS5HM/2QuC/kXZAKfWw5+Oxnv/XKqV6Anla6/FKqW7AO8Ae4Hvgaj/l2Eyt9Q7P54+BucA7SqlnMVIT3IIhsA73O/R9wGfADKXUFKAThjA6QWu9ylQvkjajIizTSofy6ryw+HKOoez8Y+uBBPek+iJzF0EQkoXKEqZcNsFO5FFY89BAE3PsudIiGQdC1Hz+m+FpVVDioqjMRe30iDK8RU3YR9FaTwGmmL4vVkodD1yMkXrga631uij68Ljf9xs8/zcC4zESd6cDTYE3bfY/E8PsE621Syl1PjAaI6JlFka+t+u01hYTSK31F0qpS4BhGAFUdgEj/fsTSZvRYn5wOL3IHNMSVOOZ+P7CmCo7BRuq7+gRKpM4ujMJVYyYaeQqmkcuyDa7GGHV+FUqOKA1pCmTGVxpAbo6r44LcSXF9MyqTPPtComLWuvNGCaPFWkj6ONaa/0W8FYE7e3DyDF3Yxh1PwE+iWWbFcX5p3eKZhmvniQeyUcVf8ScSIgnOw8UkZWeSr3MtER3RagkKpKPrbIeR3YaOVnWqolo0jAJctqFdkswEyE6lMkgvDKfJpH4yAlxIpyXl5PAVp0n4iUmQa46n2ciqc4LAULi6fbk95z82EwJLlGDqNijOvpAKZEg41EAY6ym4xeYoiR4RimxPhCcCCdwYTyISCOnlOqBkfS7A9CYQH9krbVuH6O+1SC07UdLDSfTymr8Qio2eaS73JpaqfIEjTUVWT0XhHBwuTUHi0ppUDs90V0RKgHrE6X8mZ1fXMY7czbS55imHNu8vv2+MY1a6dyYfbCT2B1bqBpooBZ+UbHLChLSF6GaUYnPk7A1ckqpm4Bc4BIMn7VNGH5s5r9NceijQLBE4ZXckUrErJFzyVs2LlTXy7rzQBHrdh1KdDcED9X5OSVYcRKgnv5mJU9/s5LzXsh13tf0WcUxbqUEO6m+RKIx09rPtBJQJcEFuXjmNxSqD5W5SB6JRu6/GCkI+mqtd8enOzUTbVHISbATL2ZtYzU+zaSi1OUmLbVqW1yXudxc9uoc/jpQxIw7z+CIJnUS3aVqxcGiUupm1IpoQiOmbDUHp1965vIdDlvKsViYxNO0UoKdCBhjNU1ZNXJaB/fNFzcPwQnLXD4ZNXJAM+ANEeJiTzg/vtOYqM7PFLOQ6jQRHPbpH7R74Et+WrWrsrpVrfAfP+/O3ZiYjsSQnQeL2bS3gJIyN9+vCD15FMJn/oa9nPLYTP47fWmiuyIkKU7vpHDkssrKI2fnkiBm5jUTf40cbpd9RUGIgGQNdrICaBivjgjBcVoFqtYaOdO5OZ3n23MMwWPI/xaG1eb0xVs4e8wslmzOq3D/qgP+k5cV2w8mqCexo8wVegFAiI4Rny+jzK15/9fNlvJ4msEJVQ37ey4cDW5lvc7KbKNWCjUNrQMFORVSIxfPHgnVhcrU3EYiyD0B3KKUahGvztRUwol042xaGYcOJQnmcw713s0vCW8V7a4pv7F2Vz7/nDi3Aj2rPviPq5SqbVUJQKlpsJRICouYcqCwLHQloUZjfqZE6k4US61YsHmU3ftEJujVg0h+R611QLATLRo5IUoS9QiJJCH4NKVUbWC5UupTYAP4h/tBa639E3wLIbD6yDnUcQx2Un3fPuYzi/UKamGpPKwhcPxUB0dusxauxC48nVDpiNlazcHJzS2sR0sY70In1uw8SNO6mWTXDp2z0C54VjV+lQoOaGzSD+jgcwMZJ4ITwebyLrcmRcVnjhW2IKeUOhp4DKgPXOtQTQMiyMUBZ01d9X2qmMd7WRxUj/sLSlm98yBd2zWKedtVBf+rmlL15ThKXaKRixdRv4Oq72NK8MNJaA9n7EQ7TJZszqP/S7PJTEth5ePnhaxv9z6RxYbqQUS/ow5MP6BDLBrLOBHCwTw135dfwt9f+ImTWzdgwrVdY36sSKJWvgwcBtyBkYZgX8x7U0MxPxacfeHs963OppUppjd/PCbkt7y3kNlr9vDMZSdyRdfWMW+/KhBgWlkNNHJmHznRyFUOoYZNNX5MCX44BzuJ0EcugkEzZb7hs1lUWn6/B5tw2wY7kUFa4zCiVvr7yIlGTogOi5uU6fPrP69jx4FiZiyLT/C1SAS504DRWutxcemJAASLTlnzTCvNr/3iOAhys9fsAeCZb/6ssYKc/4CrFoJcdV7dqKL4P6eKSl1cOWEO7ZvW5bkrT05Mp4S44CjIhaWRi+7erWUyJXC7NSl+pgVaa4tJkzwjBDDGhb9ppQ4lyMWzQ0L1wTRQyuzyncSQSEIb7AckxnscCEcWc6pSXd5HWmuK/PzWzEJFcZmLEZ8v439BwuMXlNgHYihzuckvdg7SUFqDtTb+E6dqIMdRVoN/z2TF/xn3yeKt/LZlP9MWb+VAUWliOiXEBSdhLJxFonByqtoRygzff/yVa+Q0g1M/5/wUCX5VE9EEmlaGiqxWnd1ZhNhhGSWm55OdNUBFiUSQ+xC4JOY9EMKKWun0TqsuD5Wb3llA15HfsTWv0FdmfjlPW7SVSbM38PAnfzgKXl7zGjNaay56aTanjfre0raZmhyivjqaVrokkXylE2rY+GvkzFFmvZvi8YITKh+nqJWR5pFzYuHGffznvUWs3XXIVxYqVU1A4AFPndNT/uDBtPd5Of1FKLV/PwjVF7v0AyGDncSxP0LVxikntNms3C7QEsCiTfv4/LdtUR03EkFuAlBPKfWJUuospdQRSqk2/n9R9UIISXWPWvndip0cKi7jxe9W+8rMQsXqneUvbX/NnZcCmxQERaVulm07wIGiMt75ZYPtfjVakPP7nloNop2Umn5PyRcVW6KOdaL9v1sLPvttGyc99i1f/B7di0xIfsIyrdShF2EufeUXvvx9O9e+Ps9XZn6Ee9+J5v0PFZfx46pdPl9r7zO/oypf/FNlIshVByJKP0Bg+oFQCcGryZRLiDPmObt5WmU339Rac8nLv3Db+4v5efXuiI8ViSC3DOgC9ANmAmuA9TZ/QqRoxy8+akqwE7Ngan7xl5SVP1zNDu2WfW0uhnkiv2FPvu1+NVmQC0w/kKCOxBCX6Tevyb9tVeL29xdzsKiMW99b7LhQI1QNnH3kwjCtjOA42/YX2R7T7pa/8e35DHjzV578agVQ/lxQ5iO6xMS3pqF1YPqBUFErBSEczM+ktNRyUavYZv5qrvvrhr0RHyuSYCePIVrluGCNWulQx1GQq7o/yf6CUr5Ztp1zjjvcV2Y+G/MkPL+4fHJXXGY/0bNTWZvbcIoY5KTqrglUR9PKUpNjcWmcnYwFg1ARCf2fU1YTFOu2B6b+ztirTolZ34TKxdlHLqydyz9GdOuWV7ZbvJm/wQiy/dYvGxje73hbQU65RZCriQRGrSwj+NRY3ilCaMyjJL1WuSBXVOYiG2uuS7eTTWaYRJIQfHjErQtRs3DjPpZv28/V3duSkqIcX45VWQa5/YPF/LhqF/+bu8lXZn7Xm33hDpoCIhSXudmWV8i+ghJLe3aaunA0MjVZa+M/rqqBZaXl96zJv208iDaZaYBpZRC/4E+WbBNBrgpTofQDUU+Sy9sOx2/c+1xIxfTOcDsHxBKqJ7bBTrSLYFPjqjznEioP83MowyTIbdidT7P6mZa65mlKNMMrEo2cECcsfgGe/5e+8gtgqGSv6tbGWSNXhSeqP64ygqAu3brfV2aeJ5pP7WBR+Uu2sMTF2WN+DGiveXZmQJlM5ENQLTVy5ZOzWIUZ37gnn7nr9nDRyS3JTEuNSZtVkWhHRzCNXFW2KhACMf+aZuEtPB85+3YiIazFO8+BUiymlSUOtYVqi41pZUgfuTh2R6g+mJ9l5tgDXy7dTvcjG1vqmt+B0bwOI/GRQylVTyn1qFLqZ6XUaqXUaZ7yJp7yjpF3QQhmWvnT6l2e8sh856oqymFldU9++UvWKZWAfzTLLfsKWLRpX4x7GF/cbs20RVtYsf1ApRzPf/hEq3FJJswTuVilIug9ehZDpy7lxe9Xh65cnXEYHpEmBNdBtglVG6d3VTiLRNG+z5wWAB2PY1NJlRXZ1BSqGhUPdhJcMyvrTkKkNKqT7vt8ZsfDgtaNZmEzbEFOKdUUWAA8AjQGjgSyALTWu4EBwKCIeyAExet36/TTVrfV7HBeyHbRKcHwh/K+oAtKyuj5dA43/29RrLsYV6Yt3srdH/7GeS/kVsrx/IdP1RfjrMk3Y534d+qiLTFtr6oRrcY2mLlbdXmGFZSUMX/D3hpvBeB09pFHrQz/Opqb9kWtDFLf+1woM02BUkoPOVUXqiihxpDWkOonyKmQGrmafX8LzjhF3TW/4+zeoW4bq7xIiMS0ciRwONAd2ATs9Nv+KXB2FH2o8YSTBNU5CEr1fag4XYtVOw7alv+0ahcv56zhjr914EBR1fR3+GGlfUCWeFEtE4Lb+MhprVFKsS2vkKy0VBqaVsgioRrfbmERu/QDztuqKkP+t4gfV+3iwfM6Mrh3+0R3J2E4/Z7mCYz3fgzYN8pjWhcAQ7fiXfCrZfKRSy21j2osVC38LZyCvdM0fn6SIBo5ISaY51bmxWW7Obu7gu/DSEwrLwBe1lovwv55uw5oHXkXhGC/m/chVFNMK91a880f29m4J99xQI/6eqVt+Zx1ezhYXMbIL1ewaGPVMqn0UtmRj6vjS8mccqLU5Wbqwi10fnwm783bRI+nfuCUx2c6JpUPRXW73yIlWkE/0LSyYj4ByYjX59fp+VRTML+rLAnBw7C2qCwfOe9iT4YqD6IlGrnqR6iRoLWmlhJBLhrW7jrE2O9WsedQcaK7kpSYx4n5mWQ3fKwaucgHWCQauSYYueOccAOB0SaEiHDUvDnUry5mSV5+WLmTDxcY5mstG2RF3c6BoqoZStqcCsHt1qTEOYxkQB65JDWudLs1/5u3kWOa1QtwFPbHnHLA5dbc89FvAPx3+lJf+b6CEg6rF/njqrrdb5ESrWllTQt28vKsNfz9+MM5smndRHel0nE2rSwfOy63tgQACL13cKy+1aHre5+zGZgEuRIR5KobxqJCsGeWzYKeFtPKcDj/hVyKy9ws3LiPyf/unujuJAVOz56yEGEptWkYxlsj9xcQzF7kFAyTSyFC7KJW+lNTEoLvPlQe1KQiiYEPr1811xTMTvillaCeC/CRS045jm+X/8Wjny7jyolzQ9Y1JwQvc8ojF+V9szdfIttFQ7CXk1trmtSNztQ1WXnmmz/pO/anRHcjIZh/a/PjxCy3lTk822JhchuORs77nM2g/H5OKSuM7oBC0hJqJCi7QSYaubAoLjPu4dzVuxPck+TBKYiXVSNnZ1oZnW+wl0gEua+AfyulmvtvUEp1B67D8JMTIqQippX+5Vv2FdB7dA5PfLk8Rr1LHPkl0fu5dTy8Xgx7UnmYV60Tkcw6SeU4n9kahH7QlVqCndhPGEvDmOxprX1/gkG0UU2Dad20xkE7U7Wpqcnone6XLFPajkKHgFWxuGLhaHh9ppUmjZyS9APVgkie1wH+cQCu6BeQawp/7ZcIr2a01tz/8W88N3OVpcyLWSNnNzzNRdEoZyIR5EYAZcBiYJTn2AOUUu8DPwHbgKcj74JgJtJJo/9La+JP69i4p4DXctfb1l+z8yC3v7+Yb/7YHnUfKwu7BN9h71tWyc5mMcI8T96yryDux6sqMkqx6fcMteIeTkLwUr/xUeZys2F3vu/+Kylzc94LuRzx4Fe8UNNTDpiIVt4KNs5cbk1qsqqChYhxWpWO1EcuErHOLtiJo1+56eDpqnyxULmrpjm+4Eyo91uKrWll8HFQVd6Z8WR8jrwTzfyydo/PJciLVSNXPs5slcCVlUdOa/0XcCowD7gBY/H+WuAK4Fugl9Z6b+RdEPzfVxZncY+OxDEhuF/55r3BJ/9/e+4nPvttGzf/bxG/bc6LtKdVBqcV32TnkCna5scL4h/qvqrY+5eUhZ/k25w7zkkrUuIX7OSRT/+gz7OzmLZoK2BEQF35lxEddex38tLyYp4wR7LoFMq0sjrkLxQMnEwrrXUcLEyi9pErJ9SKttkPOYtyzYJySdCG6kaw8aS1ttXISfqB0Hy6ZFuiu5BU7CsI1OabH3FlcQ52ElFCcK31Zq31RUAjjDQEpwJNtdYXaq1rdoKlGGL3InIyF/GWF5a4bJOcBmPm8soNdV+ZVMS/LpG0bFge4OXY5vXjfryAsPBxP2LFCRVx0i79gD9mwbDU5eb9XzcDcN/Hv3naqJoa3XhjDiphvrShBLFgLye31qRE9Caqvmzck88VE+YwrZrkK3T61R3Lo/SRM4+/UKaV5mdCXYsgJxq56kawoWDkkCt/zpdoT+w/8ZELSYfDal4Qp2DYTzPKC0PNzSvqGxxJ1ErTgfQBYH40+wqB+IfitnsRBXvx7TxQxNljfuSk1g1ISw1/ZbtWBHWrGgeraB65hrXTfJ8bVUIAiKryTjJHS3QMYOLdbnpo2q2UgVUj909TAJXyCWH1vTcqgtm00jnyYCDBNXLRR8NMFvYXxkYIePyLFfy6fi+/rt/LJZ1bxaTNyiacFWUnYSsWz6NITK/rqvIAJ/4+cnvzS0ivlULdjKimSTGnzOXm+rfm06RuBs9feXKiu1Pl0VhNK0uoRTplITVyAnRu05BFm/IS3Y2kxhqZ2VwePNiJmRGfL6OgOPR4dFwHVUq1ieYv5BGtx2iulHpKKZWjlDqolNJKqT429W5WSn2olNroqfNWkDZbeurmKaUOKKU+UUod4VD330qpFUqpIqXUKqXUfyraZjT4JwR329imOJtWal7/eT0Hi8v4ec3uiF6EVX3yFIxIowtGqs2MF2ZlU2X0yf8BEk7Et0RgHqqhonmaBb2dB+3NpcwauQWmnINaa+Zv2MvjX9gHC2ocZSLxakMEmg8zwepWBx+513PXxaSdNTsPWr7vyy9JmmdT2ISxuuxcHtwEKazDe3Z00hKbTSvrmDVy7vJ3Rl5BCZ0fn0mXx2danhWJ5IeVO8ldvZvpi7dWiv90dcfftLLEq9cImX5AMN9DJ7VukLiOJAmhEqm4QzzX7AS99bvzmTR7A1MWbA45Lwtm0LIBWB/FXyQcAwwFWgG/B6n3APA3YAXgOENXStUFcoBewBPAMKAzMEsp1dCv7mDgdWApcBswFxivlLon2jZjhZ2PgdMqp/9qdiQT8ao9dQrOnvzI/B38faYShdkptjKEKvNYOyPlN1bmvBf3Y0aDeayG1siF/i2DTc4uf3UOW/PsQ5GH8s+r7pgVcOaXU6hnSbCr5ta6yjyMZq/ZTbsHvuTlWdaUqk4auUiDV5mFj0Wb9tH1ie+47YPFkXc0gWjL5+AuAbFC+WmKg+HyPD/SKKNjymZfeYpJkPvJE1K9uMzNxj35Mexp9BwqLrcySdYFt2QjqGkl/ho5wxpGhTStlGtvfn9WuYWmOGC3ZuRkLmkbtdKcP9jzMd90v4e6wsFsBh6z2b8fcDIwE/AuWR8PnA0sAT4PcTx/FgJNtNZ7lFL9gekO9XoDm7TWWimVF6S9W4CjgC5a68UASqmvgT+Au4BHPWVZGELZp1rrKzz7vqaUSgGGKaVe11rvj6TNiuD/I1smSCpUsBNNqkkcDzXJNRPvZNPBOBjnhN1rd0X28i0udZNpCo+dKCwJwSvlhWEcozH7eSfdCDpbtuMqajXrWAnHjo5Qk5hwhC0nPzulVNC3v78AWFTqYvv+Io5oUifkMasD5idGJJPJYJMft7vqWAdc/fo8wMgTd0ufo3zlTs+OEpebjFrhP1fMV2HkF8txuTVf/r6dl/4VVXcTQjj+HuGUR+QjR6Cm2GnMeZ8Pp6Uss7Zh8pHLqFX+Ui1OEo2c+dlTHdN1xIPgwU6sPnKlPo1ceVmPlD94pNb/eKLsan52n+BpU7AIcp77bPPeAupk1KJRTbda8WB1mbIubwXU9bPKixRHQU5rPdz8XSn1L+AIDIFmid+2zsD3wCoiQGt9MHQt0FpvDLPJy4C5XoHLs+9KpdT3GNE1vULXmUBj4GW//V8CrgbOAz6IsM2o8f/hQknswcpdEbz9IvGnizWPfPJHwo5tR/Jo5AJXZuKJd7i0U3+VH3fvBvRhxyRVJEEVgda5LIzf0kkjF6ptfwGw4yPfAHDn3zpw59+ODnncqo5Z4IokHkyoqJVV3bSylsPEuqQsMkHOLMlVBx+USB9hlslPlFPmUAtg3u1ZWK02zKaV6abV0WTRwpvf7aIUCo/gGjmraWWprmXcfyYfuffSnwTgf+mjaFf0Xsg2qzsLN+6lXeM6lvmSW8PWvEJ6PZMDwJonzqNWagqlLjcFJS6ys9KcmqvWOPvIBdattPQDGOaN4/2FOOPAehGGEPRg5F2IDR5t2onAApvNvwJHK6Vqe76f4vnvX3ch4PZuj7BNc1/ygv0B2U7n4RjsxEkj57auRkaySl4rgaHi/jqQXAklZy7fwZ0fLGb3ocSGoLYKcpVgWun5X1uVn/fi9Ts45fGZTF2YnJHznEwnJ/y4lgFv/hqWf2RRmYvZa3azJ8Lfu8ytfaYkO01juKqnKMj5cyf/eW9RyESv5gBJxabEuaHksGCPJZfWIfdPFMu3HeCbP7aHNKdy0pAkizanMqlIsJNog8WGk6POi1cwKyLD2oZJI5dmEuRCRcmtLKJ1oajJBLtKWkOKMmvkvAsuoX7vmnnt3523kUtfmUOXkd9RbMrxq7XmO1ME9DyPmfkVE+bwfyO/c3RTqO6Yn3ER+ch5/kfyTowkHFMHYGeQ7Ts8dRJFIyADsMt0vR1jraU5sNbzv9g/753WukQptQdoEUWbUaP9fkRLWG9TuR3+L8RIJv+JtM7o1aEpc9clT9rB/05fChjX/sV/nhKidvywBDupRI1cXcofth/NXkaeqwn3fPQbl3ZJjsh5Fh85hwsz6uuVYbf37txNLNi4j+bZmRH3pcTlJjMllTnr9kS8b7Jy/SQjCPG+/BLeu+lUx3pmgSVWppU6SfPIaa05/8VcAP737+707NCEOump5HtyVJr77WROFKkgVx0m6BUyrQyjTijC9ZGrhdUXKsVdvqhjXrAoTRJh3BIxtoKLfPvySxg8eSF9Oja1mAhXByK5NLamlY5RK70mu1F2rIrz4fxyf9JvlpkseLS2PN9TlEJrzWKPRcHruesYduHxldbPRKBsnLyTVSO3HbhE2bxxPZqrS4G/AvaqPLwJuOyW2Iv86mThHDSlyK9euG360Fo3CPYH7LfUD9zf99l7tZ195PxWI6vBRCCRfPZbYhNdmoOdVIZTtXf13ByGuz5JGBHNNMbt/EAjvVbeSJXbQ2ig7PCalTSsXT55N/vUVGWWbz8Qdt1ILnmwqi53YheVnDA/Sn9Yaaxhms/DvKBg1uCYKS51cc+Hv9HugS9Zt+tQyGMmS4TEiqCDfPPimH4gBs+8kHnkPNszsfppK3f5d0sTSTI2LX6AFXzPvzxrDb9u2Msz3/xZ0W4lHc6+SX71/HzkyrwaOW1/D36d/iDvpz2Bdthe3TmxVQPbcpdbWxNea21ZTKmqOX0ripPfm53FgnXxK/J7O5LZx2tAH2CGUurvSqkjPH/nATMwojpOjLgHscM7E82w2ZbpV6fQoZ63rrleuG3GBK21rUYu2IvPEoAggkGQSJEv3BeRws34tBdYmvFvGlvl37jQrV2juB8jGGYZJVamlS635oXvVtsmgPfKjfVMw7i+So4obU7YrbiXRhDkp6J4V+jTTcLb345tVmnHjyeRzFkjmeuGSj+QjMFOzOPMbkHNbHLnpAX6fct+pnqSe5815seQx6wOkx4dxuqy0+NfO3wOhcWMKcQ82+tDm+G3lmvOI2eebNmttieCYOajm/YUkLMymMGUlZoSATPUmaWYanhNK5WDoHZsyiZOS11Oxv71sepetcDfHUhjfR8XlVZ/wdc2aiX2z8FQMTDirZF7CngRI0Lll8Aaz98XwFnAS1rrUZF3IWbsxdCcNbfZ1hxjfHlNJLcD6Uopy6xdKZWOEQTFq5aJpM2oCTStNE8glK/cV4abB2u9y9Wp35Husk66Q5nzmx1PE/n8DvfQHdVmLkidRz1VyIfpj8W1TwDNojC1iyVmjVy0/iL+TFu0hee/W8VN7wS6enofNmbhLZvkFuTsTCuLyypvAuzVyJVaHL6TezLkv8r3/Yod/OPFXOZvsJo3hzJxjHrl0K+q9cWVnD5ydhNc88vZrD1zMvf9afWuiI5ZHXzqwjOPDEOSi+SYfgtgOw8UOU4gD3giJmcoq0YuxW0fSTnRY3P2mt3MXL4jqI/cGaNzuP6t+cxZG565d/3M8nlAvCNIJ5JIgp2U6cColXa4k0SwjzWfLtnKK7PWOgfWC6Jd9zcdNAdDKSyp+otT0WC+JmbFhd1VtHt9RLKAFLYgpw3uBI7FCHwy0fP3AHCc1vr2sI8aB7Sh714KdLXZ3B1YrbX22owt8fz3r9sV45osiaLNCuDs5+b7KU1l/VJ+YXCtL3ki7U1e2XwRJ/41rXzfUP4BfirwRBHuxPc4VR6wtH3KduKtR0xgIE/AOdjJlPmbuOfD36Jasf95zW7fZ//f3PvVrJFLJ3genURgfqjZRaWszFU/7wTebOKZzKvaOw4U0fPpHO7/+Ddf2b/fXsCybQd8vnFeItGMRfL48L885p/QpXXItmav2c0VE+bw+5a88A9aQVw2z2FzP0ssGjn78RdJOpjNewsoqGaTHqfJn7OPXHTvJ3PddbsO0eOpHxyDLHgDNWQG0cglSzyL/YWlXP36PG56ZwGrTMnize8G84LSJ4u3WvYvKXMzffEWNu+1TlMsPoCVaM1Q6QQT5LQ1j5wv2EmohOAq8WmKYk1JmZs7PljC09+s5Fs/y51teYWM+fZPNu+1v5/cARo5bXlHF1YDK4NosMsN519evr1i92DEjh1a61Va69Fa6yGev9Fa62QxtP4YOFUp5YtWoZQ6BkNj+JGp3g8Y2rZb/PYfAhwCvo6izdig7e3zzUXdUqyX+9TNr/s+h0qGXNlREZ0I99BtUqzmIp1VYHTAhhzg7lof0loFmg5GSiJz64F1gmu+RkOnLmXqoi1M/Gld2G1N/GktPZ/+wbJK6yRv1Ddp4dKSUJAzT/DshKbKNEnzTpxKqohG7q1fNrA1r5APFwRGITWbWAE4uHqFJKQmL8hilf9EwI6rX5/Hr+v3cukrv0TXwShwhZjglloEefs6kYTevuXdRY7bqlQS4jC66lQl2tM0PxKmL94aNGVAqWdbBs4auUjMhuPJ1n3lk+cJP5Y/+83PQGviYOt5vztvI3dN+Y3eo3Mcj1GlxlYYhHs6Gn9BzquRC9FAiIThVTFOgXneuMLPT3rAm78y7oc1/LjK3rrA7b8Qp/1NK2umIGeNRBl8TNi9/yKxBEi4h75S6mGl1MPA5Z6iaz1lt5rqXGiqlwGc6P2ulGprau5lYB3wlVLqXqXUnRjJy7cDz3sraa0LgUeAi5RSHyqlblRKvQ1cAzyutc6LtM1o2XWwmO9WGMJK35RfabP1Swcb2vLP5sAUAAcyyy0/Q0bsclglqEz+2FruNxIKf7+4v6fOD6gzLX0Yt9f6hPfTn6hw36Yt2srkORvIKwgdwj4eWEwrbQbCht3hmz0++dVKtuwrZOfB8lg9/uPDe4j6qnzFtpZKvgevud/mSdova3fzr9fmstATvKQyKLbRyCVLrik7dh20i9VkTyiNXDgRCe3wvzxWn6bQGjkvlak9MD8r7RZ4zKaVThq5/YXlwkHbxgGZaiws3ersAzxn7R427kluk2cvTr4hZhx9vqM8prm92unBg3F7fVz9BTlzHrlY9CkWOGkzzOd7sKhcsPhwwRafILH7UDEjPl/uqe98DO+2xZv2MerrFZYxW9UJnhBc20atVCE0csEEuX35JfR8+gdufc95USYZMb+//OcIq3cGD9KkdaDpoFlLXFMFuUj83iq6lhJJ+oF48bjf9xs8/zcC4z2fLwUGmOqcQnkuuJ89ddFaH1RK9cEQsB7BEFRzgDu11hbjca31y0qpUuAe4CJgM3CH1vpFv3phtxkN174xD4AOagsT0sfCEth54mm+7V6TMvOD219jUpZSHovFP3qQ/0q5Owk0cheM+znsuo2VdXXI/9wvSfmJI1IMTVwrtZs2agebdMUCTzzy6TK+WfYX797oHIY9XliDnQRur+gv5v+be1909UyRKpPRtNLl8KL512vG/fNLmL4hscArTJhXMZPZtNJMqFD/tSKwLY4kYbP/qr9/jp1k1Giaf1/vJUtLTfEJ8ubJipMgb54UH1av/DmtteaTJVvpcFg9OrXMDtmXf71ujPMNT/0j/BNIEP4+37blTqaVMdDIpYWIIOv9XTOVVXBLcdlHrUzk0HTSln21dDuntGkIBAp7uw8Vc1j9TB6cttSxXUsETM8xLn7Z0HZv2VvIS1d3rlC/k4XgPnKRRa30ohzTE8BruevYtr+Ibb9vZ/y/IulpYnFVYFHS5Q70kSv1Sxhe3bF7a5pPO1R6gYo+YxKukdNaK4e/dqY6A4PUm+XX3hat9eVa62ytdT2tdT+tta09mtb6Na11R611htb6KH8hLpo2I2XlX4bd+w2pJmvOgnKfJmVjWukvzKTq8hdQJBq5JJw7BdBEWVepr681w2IOMTJtkmX7RSmzY3Lc2WsSkyPMTiMXS9OXsDRyJN8KmlO0wETg1cSYNTK5q3fz3fIdAaaKyYD52oV6PqSlhP9KiCjWiV9di49cBBq5ysSsZPNqKs2CbkGJi+mLt7Bhd77jdc0rtBcOvvh9O3dN+S2iRS2oGukJKiKwmRcH7vhgSQRayPL9aoUwjy/xTFr9F6xS3PZRKyNZsIg1Tosur+Wu930u9vMP9pp820UptsN/7H65tMLx25IGp1+uuMzFxB/XWeYSJT7TyuDvP+UQFAes92dVMlmtyLzQfyFOo4Nq+Kojdrepk9LE7nlS6T5yQnxIM5uzuco/+zvZt1Pbaa6skeZqmV5A5hto1Y5DvJSzxhely9+EKRE3WKTHbK0Mu2y3Lr9TPkt/2Pf5F/dxlvr/rPVDBXoXyNpdh7ji1Tl88Xvl5JezC0ZjCYNe0fYdNCNmHzn/RLnJgJNGLhF4I2T6r1ze+M4C7vxgSQJ6FBwnp2s7ItPIRdAH/+xifhq5RE6WnTBr5LyygVlIeH7mKu6a8ht9np3luIp9wCTImV/WOX+GHyreTH4SLhQEI1ikO9v6fsW3h3k/mfcLZR7sNa30LogWa8OP0TxBt/ycCRya4bhsl7isgkckAXYguf17K0owjeb4nDWkmn7cMh08/YCPIKaVVi1M2N1MOBV5pwYEO/H7nuj3daJwGgt2Q7LK+8gJBkcqk6BQWj6pLtfIaTqrVfyQfi+dUjZY9q3ltveB6jv2J0bP+JPHPXbyTpP4yiQSe+naFHG42gfA7aU+l0k6pWygKUa5f+SxFmqvZZXNDoWb61O/pptaEbIPd3ywmF837OXW9xaH3e+K4PbTVIBVYJi3fq//LhHh/47ytlxPJXfUSvPYTbQ/mjdCpp1m8LsVFQ+4E2tcIVYDzaSG0Mg5RRUMtfocqJEzv+iTc9Jjvhc37S3k7V82WHz0zM7/BQ4C1nqTT+vmfYV8snirMW6i1DAno8bXn4r8lP77rgwzQb11gTL49fQK6F5BLt+TJtaikbPcM4kj2LG9fSwps9YKFfAMrJPEaizHOV6/L34ztI4pymxa6Xn2hbh+yuWskTNfy6okIFfknaoDNHLW61CSYAuaROFkTuk/LLTW5BeblDeeezMu6QeE+NJGmVZoi8vDDHt/TK3hzlpTSVGBN1yqaSXRLjT7Vx5TCf+VkURMniIJRXuE+sv3eY77OJ4qvcr3vV+qYc/fUBmOuO+UnePbZhGKbbgs9SeGpU3mw4zHUSGEvvW7KjfAQJnFtNL4b57oOYXUDhd/Yd74qi0+cslpWpk8K3wFJcYEsKqE7bb6zQZuN5uARBK0NRKlRWCwk/LPrirgI/f5b9sY9tkyx0AQb8/ZaFtuZtfBYu6csoQJP661XC/vM7FB7dARLvNLqoAg5+AkF5bfWYAPb5jHNCd2DnFfek0rvVYwBRi5Q1Pcpb7jJ4OP3OJN+wIiCJqxy2dpfDc6HGxF38mPsaqw62Axd09ZYhtJMZzz8Zqsen3kynQKbu90OIRGbvaqbew8UGS7zd/3t6pQkUibgXnkrJZfVcEcPC74XRObYgDu/eh3rvHEyoiWsAU5pdQqpdRQpdThFTqiEEAdCmliCuqRUrjP99mnkdPa98LxMtt1PACpppXEA0WBL/qMNMNkICDQRQIeNJEkh/QKZAd0bfZQnwmuC3zbGitD2G3o+b9UH0GRx0SmrV8aglNTlvND+t1cnjoLgNFpE33bzkv5NWgf/AWfeGMNduLRyMVQYAgUgjSZlFDLtDKZppJvsugUtTIReLXKdosmAN/88ZdteaIImVvSNMYjMeeIZLIbNNhJsvrIxalTUxZstnwv8jwT+53UIuS+K7cfDFkn0YQj4DubXAZpLNgxI9AAeO9bn0ZOm96rnlxyoXxa4s2WfQVc/PIvPDT9D8c6RSUeIcRPg+R9VtbNcI5lF22+vmThoelLmbZ4KwPeDP7+dj41Y4NXkHNRLsiFilo5b81f9H8ptC9+OJd1894CXvx+NTsP2guGlYX5nZpXUMJdU5aE/R4zgp2U77965yG/hZWaKci5beZyEHi/+Udw926O5LkTiUauFBgFbFJKfaKUukApJRq9GOAfmTH10NaAOnYPhf3UMerr4KHyvT4DgRq5yn+Ae/2LwsHrH7dBNwMUmhQ+KOsDlGswG2Jo5PbqemQqY7X8xTQj2GkaZXyYPoIP0kdyZMpfPgFut67vO4ZFE2pDLIWocHDbaE9KwzCVCbt9G42cfxjuNJNG7s2f17MmRPjhysD8M5gFqFCBDeKBd8Xb6QV18/8WOu5b5nIz7vvV/Lx6t2OdWBNK8LX6YIaffsA8y45cI2ddudZak0EJY9Je4cbUL0O0VjnEa8Ggdloty1X2JgEPZyTfOWUJ+wuSOzy8VcAPU2BzqB/uZMZcy2mBxYt3vHt9gS0LpB5BLtEauRVhCOwFpUb//U0rvf2tEyQNw0s5a8vrR9G/RLNkc57jNh2GEO4df143DDcpuH13YPDxMzJtEvUPrArZx3DGzcUv/8JzM1cxeLLzO6MyMJsjfzB/M9MXbw36HjOjtfVcr5803zJnqBmCXODT2zz2rDnlwiOSaV/YgpjW+nigB/A2cCbwKbBZKfWEUqp9+IcU/PE3ZUspKo/U6F0hd2lNut+E+4A28hLVcsh/42vP20YymFaWhD86m6o8AHbohr6yTfowANqpv8iiiCxPCOl9up6vTh1l+AyeoNYFJE//Mf1Oi/bzgbQPuDDFPsmw1rrStT/Wm9/4HEtTwoColQT6xJmjoj72xXL6jv0pZsePlp9MJjTm3yQjRKjxeOD9XaIxrXx33ibGzFxVYVOKaAnlaB29Ri6w4doU8Xn6f3mq1kT8X1/+zvBuDdekzuTS1FweTnsX9q4PvyNxoKCkjEc/XRaXtv/ccZCNe8tNmcvcmv2Fpew6FF6+v1U7k18r58XZgtJ+S4BCLgqNXPl9qRmY+g2np1jD8HufH+me926+zjBttNPIVT71MkNnhvJat/hr5Lx9r5ORail3vOZVUJIL+zkVYsHATiMXagbdSu3mlbTnQx46nIXy3Z57fvGmvJB144mTrBXO3MOtdYDVx+e/lbu31FTTynA1ck7ESyOH1nqu1vomoDlwI7AeeBBYpZT6QSn1L6VURtBGhAD8g3OoMrMflCePnDtQkPNp5NzBJwDJpJGLxEeupTK0Ftt1Y1/ZKt0aMPLueTV23jr3l95k2ltzmEcQNNM2JVADNy59PHZP/ET4QFmdpQPLmtSt2O3l/5vbjSv/hYVE+6T5Y+6P12w43gyt9T4bMv/Fg7XeNQWhifwFNW995ae1CHWbRxsVNdSouCz1R05I2cBVtWb5Jsjlxyz/7A1f3dRsmbDyiwh6Eh2lLrfjJGPcD2v4tYKBhYJhTmBfVOqiz+gcvloanilTME1LchBoVeBcw6/cb0O4Tx47U65zUhYyPO0d3k0fZXnH+ptW2mnk/H1+khGvJtdf4+E1lfZPjO78HE/O8wtGuIEgQp1xqkkj580jp3Ro1wJv7tpgVCUfOad3WUEYPrlG1EprWYnLfD9WnesQLXYLC06+wqGmU95nmWX4hNgnquVsrXWB1nqS1ron0BH4AOgDTAa2KaXGKqXaRNN2TaSWvyBXEhi10qU16X6+Swc9GrlUXRY0aIe5DTOV9ZyZMn+Tz5TMTpC7IGUOfVPmB5R7BbXNuqmvbJVuBUCGKuP/PNo2l1bspAHL3O189bLJ53AV/kTs0pTcgLJgvhardxyMy0qTXdQry/1cwR/N/3mtIWBcJVuwE//VvvySMmav2U2pyx3UtDIVF/MzhjAm7eWoj91ebaW92sqQWp8DMLjWl77+RPNTJEYoDm5qZBkTIZa6rWPR/rOXRqpcc5RSag0aZA1eY+yfiWlB6kB8c1m53Jq/j/2JXs/8YBsJ8o+t+232ig/Ltx9gXwTmkum1Kt+cOBLCuS/C18iFq5Ir/+h9Lh+jyn0RzQGwvJPMWr6olWZBrjjguIm4Y8N5t3jfpf4TZW/f0/2sFbzv/wDz1Wo2zw7ndPxNK11mQS5IeoFISLL1z6A4rUmGE9PAP48clKf4gJobtdIpgmkoAT+acRO1XZJSKlUpdTHwHHAlxv2TA8wFbgVWKKUuirb9mkSq38RZlZWb3fistnWgL5P5BRQsZLxXI+d/s1YkUlG4zN+wl6FTl3LNG/MoKnUFPBjOTlnI+PRxTEh/nlbKHIFK+75vMQlyW3UTSj35Xm7y+NKUkYqLVEu9VmqXL3VBOIxJf5VT1GpLWanDy/St2es55/mfOPrhr2N+De2ENvMxKhp8xU6Y99fI2Y2lxZvCv5axxv9F8MqstVz9+jzu//j3oILR7bWm01Tt59LUnzmcyDVhLdjNjPShfJ9xn6X8+I3vANE9cC2aqAS86e2GjyXYSSRthRAQlaksxVVg2ebyG9Naa18EWgDyQkeBrAjb9xeydlc+Ow4U87VNAmSnRMzxYPqiQJ/oYCT7xDuchWRHTV2UJ2feyxuM6AC1fWVHmQS5qQuN4AK+qJWWYCelAe3FQ5IrKnWxJoiJbDh+RYUOGjnvreW/yOW95wIEv5BHSj7CvT1DjTOzaWVpjAW5ZNXk2uGkkcsPU5DzP9eaKryZcfSRCzEsfAv4EQyfiAU5pVRHpdRoYCswFegKPAscrbX+m9b6Hxhauj+BZyJtvyYS4CNnk0fOzgTuEFm+zxk4+8l52wi0pY+mt5FhNk/ak18SEOzkqbTXfJ/Nq6YNOOTLbWbWyLlIZatuAkA7j3lDhkejtJ86HNTGNWmldtHMo5H70tWNP0zaOoD2RZNpV/Qem93lbX+UPsJSx+lhNNyTlw8gzyEcebSESt5cUY2Oy60pKCnzvfw12uITB1BLBT68b/9gcYWOWxH8f4eDnsis0705uRzoqsr9I+urAsd6TnyQ/rglmqeXU9c8D0QXzc6aXqJyXvShDmPuUyyjVloEuVLr9fc3XXNraIhpYhtnQc7cX7t7qjInYWt2RRZMyNzd5dsOMOR/C1m6pfI0iKEIJ9hJzE0rTTsWeRbgzDlG65ryZHpTuKTZaeTKDI1cvKNWXjVxLn977idmLrc30QtHI+c1rfQPyOVdIPK/l51Mwv/Yuj/pIu3GilAJ6c3BTlyeBeLyhN+R/+6h3t/JitO8IlzTSv+9/fMFJ2LRMtGYb7OIfOR04D6hiCT9wL+VUrOBZcDdwG/A5UArrfUDWmtfGCSt9RrgRUCCoIRBqp9ZpHnSo1AUlJTxwfzNAZoS80piRjQauUqYrJiDURSWWDVymRRb/GJq4eK0lGWsyBjIG+nP+so3aGvGC695pZcPy3p7Pim2eIS81moXLZShhVmrWzCwZKiv/nFFb+LyrL7dUFqubfGftDu9TGunl/tlRZLgPFLsVmYq+kDcX1jK6U/9wN/H/oTLE/Y9WLATL5UdvdNMsElNMPv7tiY/hjpEFt55fNoLtEkJzFHkw1UaVEBy+p3MgmdijSzLMT8XQspxDsKb3bVIMVVOLbOaVvqnH3Br7UslAkBB/PzTwBowJ8XGPDe3EqOK7joYXpATL+bJ6RUT5vD1H39x4fifY92tmOA0xp3uD/+JdxSWlRR7nsnm51pdAvNvlvvImfyObX3kwutDJHijLj4/0z76YTgajaLS4D5y/v323uf+z8y7P/wt7AiFVQ1njZzx3/uMcqN8ppUpHh+5tAq6GFQFHzmtNQMn/cplr86x3V4QpWllsd87u7pr6Ozem04Bk0JN4WxdakIcPxKN3GvAEcBTQHutdV+t9VStHT1Dl2P4zAkhCBDkTMFOlDIc7wEylLNppf82S3sOPnKVLcgVlbosPnJ/9/OLS6OM61O/IUuV0CXFMHP8SzfkkMlEBmCXbmD5vl43933e7Ilq2VbtoLnHnG67bsxusjm+6A06Fk2yOLev1q24ziTk1TK9/P0fRl5OO7I8+EqsBTnbYCcOKvpo+OL3bewrKGXtrnz+OlCE1oEaYTtBLpwHerwILsjZb0ujjMMpFwZqq9CCXF0K+DL9QWak388FqYFRJS8vfrT8y/7NQVfWnExgS8vMv2UiTCsDj2nua0oEKrlQppXm51pqqXUibfUZMP4sppVF8dUwmcdNJOccLo3ZT10i1wKHg/kntPPvSzSWsaDtyyM1uQx5TNN+XkHF/E5spAITa9fyRa20Sz9gXkGPrk/hUCvVfuw5vXvMFDn6yHn++9V3ac2+/BJ2JThnWSyoYNBK3zWyM630auRqBVkcD4eqIMjtOljMrD+dFyzDee9rHTgv8V+cOlBYGpZ2rzphEcSi8JGLxCokEkHuEqC11vohrfWGUJW11r9qra+PoP0ai78pm39ggHUe0xt/zckhbfaRcxbklC9qpX2Y4nhijiq4YU++ZaXbP3F3OmXU81s5XesOTJLr8hu2600au7XaqH9cykZfsBNv1Mt8sigiMOqjN6UBYAmQ4iRAmP1nikpju9Jkl6jVYgYWw9/M7dZoNKl+mki7lcim9RIXjDaYIOeUHuJotcWiYQ1HI3d6yjKOT9nIMSnlCTq/cJ3KSndr/lNyO8t0u/LKhfuCCtVOP9OfO8q1Tv95d3GlhGYONWLM2pFYmlbWNl3zVJf1mWY25TGeQ5p6ZsGn5JDPXykemK97rFMRXpb6Iwszh/BH5o1Bn8vRkuwTRGuwNgfNm8MpRLtQZd7NazpovvbNyAvYJ90uamWZN9iJfdux4OOFW0LWCcdHzvsuCPSRs5fk8ovLOGvMLP72XOLTyVSUoD6sYfxgPtNKzzvCrVN8VjpeH7mQGrkQ92GS36ZAaE3Z4MkLHLfVpogeKX9Qi7IADft+P5eTbk9+zxnP5NQoYc4ivFnMLIPvZ6eRC0Ukglw/DH84W5RS3ZRSb0bQnuDBP/1Aik2wEwgU1vJNPnJZYfnI+WvkjJfKszP+jJtPSKrpgTvs02X8sLI8/P+RKdYgA2mUke8naK3RgYLcbp1t+b7NlJ5gpdtIT9AlZTXpHgHZ61PnxDbT9pamoBhOL1PzOySSBOfhECpqZUVNK/0n33YaObuVyN5HNw0oqyyiMcto5ZfovTahzdeOUIFBL24tvZ2/lzzNl+5TKSCDEq8fReG+4KaVno1lLjc/rtpFXoFxf5pfcN+t2MFHCzfb7h9LQkXgiyQhuOMxbMrqmrSg/j5y/uPcrW0mToV5UfUlHMz3dqpHkjtYVMqTX63glzW7adUwy2nXkDybNsH3ubUKTHdSUV77aV1SauK8hKNtc/adi+75ZuebZF74PDJlm/8uZHpykBbpdIq1J1S/Z/EgmrxP4XLvR7+FrBPOAo/P580h2In/tVwRQXTUffnBc9NWFUL5aNpp5FLcxjUKGb25LPg7JdkXXCC0RVGwhepHa73De+lPsizj3wFj0I7dh0oq1WS9MrFbWHCKWhnqeaI9dXJWhv/uiESQG0hwn7cjgAERtCd48E8/kOIq9gl3Sinf5MpfI5en6/o+ZwXRODjlkSstc3PvR78xPmdN2DmMIsU8gI86rK5lmyW4AUYUMX+BdK2NIPe261xWuVv6vv+hj/B93mzSrnnZrhsF7WMJaez0mGu2UOUPGicBwnzLxl4jV46dij2WLwevbbt/1FRDALYeJ5FJPaPxz/PPIVhHFZGCm/FpLzKs1tu2+5yUsta2vBzly91IYV7QSaf3Z3rrlw0MePNXBk9eyPb9gX46eRGEnY8FoaJWhpLjrBpjy4YA6lg0ctbnk1UjZ4zFAO3VwfilIDCbo3lfwh/8upmJP63jX6/Pi5lzflNlmIj2TfmVW1I/JRb6nU+WbKPTsBm0e+DLCrcVD5zMEsPRcsXCtNKLOQDY/6UE+qJ5g6EUkU4JaUahK/4auXAI53nrfS46uUz4D+FI8nn987W5YddNZhzHk41ppX/6gdCCXODz3ExViO9RWBL9e/2qWrMAw4T5zF3heVEld+KU2GJNCF7+OWSsE62Z9ecun0tVOESdfsCGOhAHO5IagP9EGsrNklJTlE8D5D/R2Us9SjFWEmsr59Uhn4+c35PFLKhs2GM1fYqWg0WljgEd6mRYE5Sa80yBcX7+57HaL7AJwH7qcm7JaNoVvUe7ovdwm4axnSDn72Nnh1er5w2QAvDgtKWWOt7Jnfn8imKukTOr4wNfyBV9OfgLhZrAhQQIfIklUpCLRnht5pd6ojZFjE6bwAWpc7m+1gzaKuvCRQpuzks1fDZ/cJ3MCndrLigeGdDuPl3P+JC/OyyN3FNfrwRg3vq9PPLJsoB6lR6i2uZwFtPKiJrStp+91DGZSSuXdYHGP6/OgYLiwAihpfHxMQO/oDOevsxcUW7qnergu+TlaLWZpuwLKH+4lnVC86/U7+mgtjAhfSz3p03hg/TAMVWdcTKzjPWwtxt/6X4uC+38NO5eQa6YNErwauS8wU4SOwuPRCMXGNTEW24v4IXDyr+cUyNUB+yiVnoFObQnWI4K1Hp7o2IDUBq4eB5L65nKoMQVm/nLP3a9Hla91FjbsScx1mdS+Ivxbjd8uzwyxUpQQU4p1UYpdYZS6gxPUUfvd7+//sAQIHwRUvDhH+wEIIvylUGlDGHPf6JTTDqFHvv+rCCmY16NnL9ppVnTEYsJ5XfLd3DC8G/p8NDXti+TQ0XWB2MDZQ27fYzaHHAev7o7RtSHXWSzxH1kRPsA7PNoN6+tNdNXtmantX/elU/zdSyOdbAT0+fyGz52L4SA9rX9QkKAIFfFok4d5ucTU0cVcWlqedJ3s8AOhl+Tl1Fl/+K8kqf5QweOI1+gnUM7gt4z3t/OHOF0rU2Y+cq4rKFGjyWPXATv2VCrjBbTSrd1Ecr8Mtuxv8g2wA6u+Jl3mcezty+ZJn9epwS5AG+nPcW3GUOZn/kfixlyLcq4sdbXlrr9UucwM+N+3/dTU1Zwogql+a0+OAVqcprMRJ1HzmY3/+fa1anfW75787IWke5bEPXlkYtgBT0ehOMj530P+Xev3LTSSkVT1yQTFc4j5/lv0chpf9PKwGfSucWmjFohFpqqgGUlJWXRddIu3VXtMPzQq9EQDInTAnx4PnKRCbyhNHLXA7MwEn1r4CHPZ/+/acApwNMRHV0A7AU5b8QtjUahHJ3mi0gHwgvm4L9CVGJZlQ67u47c+E65Y+ybs9fzwnerLUKPVXulaYw1ktg1tb6nY4rhM/R86aUcX/SGzwE5fBT9S0byqasHANeX3BeivsGf2vCtC5ZE3PsiNL8QK2JaWepyc+0b8/jvdJPmz+aGj9cLocwT7MROI+dvxhtrX8BIiOb8m/sJav4+cscoq2/asWqT7/Nq3RIn9uExDw4R7MS7ra5JC22XdDWWwWvCwU5zYR7PEUWtDOF7Z9bIpbitL37zMfcWlPom1dZK8RPkSk0aD++CVqYpwq5TSoBj1UZ6p/7u+97elPuytQqSrsLElamzgm6vTVGFI+YlEkdzyhDjBSoQ7MRmP//FKHMwnVqU+RZGi3QapdqqkXNaTY81Trd/cTjBTjzPkwCNnE2QLAhPOKwOhPNrea9Rqo1Gzsm00q0VRV4TXMBVEty0Mh75B2NNdAu0OiBQHUB9Qlt1TZkff5/wRGC3AOXkEhNKI6eJXJsbSpD7BEOY+zeGiPgacIPf3/XAZcARWmtJNxAFdrbY3omNVyPnP7H+oKwPgC8KY2bQ9AP2Gjmz+UYsHjlXd2/j+zzyyxU8/90qHpr+h6/M7Fhbl0KylPNEbb1ubgnmEil3lN5Ku6J3yXGfElb9ee5jfZ+dHkgXjPuZT5dstQqnfhq5+Rv2cvHLs/llTWin3q+Wbid39W7em7eJvfneCUQ50UQvCoX5GVLm0rjd4WnkVm5PnKlNNGZOAT5yfgsdXfx8ZrwrjDNcXQm2GrZflwty3hd1Ki5uSf2E01LKTSe9D3GzOXGDrPSA9irb/MbuUlryyEUStdLSro1ppUkjp/w0cuZ7qLTM7aCRi5+lvlmQ9Ha9cd3y38dpgnN2yiLL9+NUeeJyc8Tbz12nOh47WzlPeNqqv/gl4zY+Th9OYryzKo5jpErzZ0eNXOyO6b9AekRKubmS+X1aYmNaaf75K3OtZdWOg//P3nnHS07V/f99kky5/W7vsLBL770jSBMQRcFHReWxodiwoI/YsSGi2LCgqCAgIKKAFKX3XnZhG7C919vL1OT8/khOcpJJptx7F31+D5/Xa/fOZDKZzOTknG/5fD9fnlvVXV+NnJ+RC5+gTFg3khR+/zeiqmhlKGBQfZwZfkYu6CMnPGplVHzpSWdPcpoYWylf3XH53/BzlxosmZhAH/9If517M1+ueK1d1KbC37+k0gH8/wFxlzosdlL/sZZtGWS4QaaXVe1FKeVLuI2/EULsCPxNSrmw2nveQONQhvSwzPg1YlnfkZMIEc7IvbNwMS/KXYAgI9dEgTaGKWFWSOyLhBq5IU35LG2NvlyyLZuq+rreQ26iCPpELXZ2ZE9jdWjf4Zg2AY2jfqt0vhPo+MwSW1kkWyr2WbZlkM/eNJ8Dd+j0t0UduXd5jTXP+f0zrLr09KqfqfdoURmvsLpR+O9YQF/Y3IxcvMxy1LBesW1saihHgpF8fVV/OSCbaBM5JkUcu13E+tDzc6yHANihhsqgnpGT3nA/z7yL/0ndDMB7i1/jKWcvf+Ju1hy5A3boZMH6cH+01yMjV+sj9DHXiGplkiDEDmIzRxqL6NACIiLilOl9sgpluyJQBQT1StvBIrJjIqQps/YcqIshgdvm5FbnGAC/b+UmOY7HnH04w4wXjHir+TSfKX0aGRNHfa/5IJ1iiP3FCqbRzUYmxBzhPxtJ46Kegv84w1s1z673MxVUMGqTHMdU0cNhxis8kL6Q04o/CGU8y5gV1Eo75AxsP5Rsh7Xdw8wa30yhbHPyT93WAHqv0iTYCRxK3wmN/ChXPbpitKf7vw6NUCv9WnvPkdODmfOdOfxP6eMUtIxcuVjpuCQpFf6nopGMXDuDvJD9ROLrHXVk5CCwaf9/R1wrKai9nq3cNsTKBu2tuq13KeW333Ditg/UZKI7L8pxU5c8oxXebqET5aQota2Joo/HMp/lgcwXK/jLSaqVuoR1ZgwcuWifuijWdgdUhIkEBu0XSx+v2HdsHLn60UObX8hcSzI8RK0chQiITnV5bbNbPxW3EIwlRSOckXNc1UoR48jFbPt3QV8QJ9PDJdZVHCgqVegCSDpxf88l0s0S7xwROnCvceXv2iNbK7bp8JVic92+YXqyGVCKr01dGjrn1kxADd7SX0nXi5vUpZRj2mi+FkmsEWcyvGtl0AHg0cznuTT1+0iNXHhOKoYcOYd0HKOgXGz4/OqFfg+r49djeB1qvBp6fp51t/9YZeQ2yfE85exZ8V59bE2NEUoBQhTTPY1VNc/nPxGJ9WUNZEp0nPmrJ2p/Zsw2lW15xN7P3zbH2MjHzDtDwasSVtAMWmXkxrjsAKBvuMSHr3kutO2VTQMcc9lDXPf0anqGgmv/1Iqu6NsBONe8h1XZc7jYuoaSLXnwlc08GpF0T2Jy/DuDcf8uJF66GLET1Z/WsVUfucA+enfxG2xgIhKDghfBs/O1auT+8x25Rui2xxjx5r/qZxzVPEhCbox1BcYaD7+6ha/duqCiF141xKpBJ2T1t0emNtF6j4ickCByUvFv7E/x/3+ohswquwZajZx0VSf1jFxRBlEhRQk5xlhApxhihuhiL7EqdPwk1cpCqCnu6CMkjVA3Jgq3Pq5fNrNYzmaX/LWh13Py9W5ALXzFyx1i+N86qlErG8GMzoA6qgz+sDhAfK1DPajVPwe8jJwMVCuHtd88mpGb1pHl3wX9q3wzdS3nWA/x98zFifu3kfMd0SVOvCPXIgqhGs1+6SqbXmefVPVc9PYD6tfs07K36nPVtWtJBxm5aDYO4gUIPveX+Rz43ftYESOOMlrEjYsxaQju/Y0rgodKsRO9XjBfskPjTRlKAc1t7Fe+cM2C+7fWfdZCjrleP7JXnUo13WmeI7dRjmetnMJlpf8KvX5R6Txt33hDXVdb3V3876wnCTvElb8z1M6UNIr4jJw7xnpoC23f2dgYyraEM3IqeKCf09iMv+ufWR3qo6rjG7ct5M6XK3vd6WhlmO+k3NYpH7TuZV3XAB++5nmWbAzXmo9m3VDYYXxtped/J+q1VxrpI1f2HbnKjFxJI6/lPDvNjsnI6fjfQK0sNBCIjqW/A70eS6VeR+7fqYBdDz549XP8+Zk1fO/OxQ28Kz4gq9BIjdxIUC0N8zDwkBAirT+v8k+9/gYahJowStLEFq4RE2Tk3Oh8mNMfTCpqgtEpP9GMkkiokRtrxcVGDK4ZnjCAkv0vYfE3+2j/9f46WgaMNdb4jlz1jJzuvDUyEUZhaVQuJbgQF7mJ3vj1UM2SdtHfW7YlUkrf+NazoNEauX+vbHBwzm81n/Ef7yPiqUL6vfCSR5k1ROUP8kL2E8wSm/mmda3P798sx1U9E+W05Qa6/doyfYFb6Mx2z9j7ON3eiDMq4rJNt8/fwHDR5pK7X6l6LvWiVmR4xAIT4Q8BYDzxtZTZQthx0RVzC2WHjPYbDnpKvNtTCj4cLVUZueT9J9HLouxH/Od/sE/1HwvPGFTzxgY5EYBf22fyvuJX/P3ucQ6m28vKzRDxNbSnmc/6j2fWKZ7yn4a4+kOIUo0S3jzia135PlWyUMbgGU392EBGHDmjglrpJHyH0WBhTCBHx/fuWpL42tHGAhZmPxraVtoUv79PyR+FA6rXi/4nom5HrsbrKojuaNRKNW4sPygnQi2OVMDdqenI/ed7co1k5NpiauAOzF/pr4n1Uiv/0x05hXoo3Qpxl1rf1EhD8JGgWo3ch71zUaHUD435p78BQI8KmdhGBtMu+T1upHQXRj0jp0eHCtICAeO1aEhUeTEpI5cPZeRG/z0aceSmeDVLerPuP5RP41TjOZbJ6ayQ00Z/Qg1COXI7ieo9PLqGgqzDaDJy+g1tx0RRZUJktexI0jUuWNIionPiy46DJGhavFGO9zOl0ejbv1O6Wv/oQZn1KXsnmC+yoBy0CBhHP20i56sH5mSal+QcquG61KXMNoIM7KYazeOHPCcjbQ8jpftbqt8MAqEc9fvrDotOZVaoNqfXoiqPBHEf18i1TWDK+duThDx22vRPePYqONTNSoVaeJQd2rT5bVhmmSAGgnql7VEjp/22wfGTP+e57Cf9x0ucWSxzAmXTNGUKpP0s21o5yX/tCWcfZuf/jKLCb5QTGC8GYzNyTRFBHqUMN0ts5mLrWh5y9uf6Ghnj/wTo1zZkzGjDWd0f+ZJNf77E5LZsxf6NoFpGzsYMBUIdhG+kA5SlRTGiWpn0HUaDRsaxEOHvdH36BxX7XDb0Ne7hN0RrwaMZuTcZL3GksZCfls+uqJ9Pwn96Nqna6tfIqftiJzKgVip7TNFvSxHl7JxMgwC7UMOR+1/grzTiVLVrqq+75a+hEFFMP9Z4md/bp7O7WMMcsYG7nMOIu1KjCX6/nhjpuuhvi2F9JO07WiQ6clLKayLP/7QdPv8NEEwcZUyKVjNpe5BWT7pbAvcv2cKB2sJT1Apuc45FVKE/KuwgEmrkdMWisZi4Gxn4kz1n0+/LBSyWszmy8AtyZGKFALY3lCN3lLmIt9pPcadzROx+vcOaUz0KSWcnzhLWX084dLXfWUrJhr48ExMiqrpjYTsSR0q/d1+vVsMTdeT+ncFF9dltDIfqrnRVOoHDvOz5APzLPgSArbIjNsN2n30gJ5mu+qDuxAFsYGLVcxn26gFMIf26L124p1MoR859rhuEQ8VKp7/atdwexpSUlRHBkffuqsxa6BLvFbj7i4Ejp903+ZLN+GoZue2w7tshp8L9W+/PsFjuGGJFpDxHTtEiK8dcYMxskBPYi9UVYjsQVsAE2NtYxe5iDf/KXATACeY8brTfPIKWLK8vksa0jHn8lp89yqquYe79/LHsOqVtFKqVlVC1v7Y0QoFQB1GTWrk9Iuj3Lq5fsU//yMNEfOatQ/azi1jPUhmm+eqNwgUOf0q7XaG2yHH8wT6trs//T21mXbIdHl+6jd4665cSKbzedp1aqe4rU0hA+oI45cj91kUHO7EZMVT9ejaSkft3aH84jmzIkRvnCYg9aO/vO3EQMMTU39+mfsKOxhZmlN7L7+wzKo7zv6Un7chrx12EqeS6Uzf299brby2/gQqoRcXBoGy6dVNKmv/BJS5dJ62JnegRolKMLz5JhCkclqGolcENtJPYyDR7nf98LKSJGznGJE/sZCsdoe29tIUmidcTqkYO4JfpK+p6z2jmpBC9S/2NueErM3LJH/rN2xdx1KUPct1Tq2Nf19/rGvWB0zZMUAcXpVb+O3viqN8kSnnVa9x0GtpbTFdQoJs2BiMU3a+XPsR5pS/Gfs7/aDVMSRjUWmJk7GFM7BCdsF242xxHMpAvhRz9OAO32mIxVot7lN4WPY04Bce6jht67D5rFdV7KymE60wdf36zpQiyBn52ZOwX/tB3duLvswDhF5Y700PBtDRlOhikw6MeVcvqqlrNd1mPVrx2jOn2k3Ske+HbxTA/S/0qtM+bjXl80PxXYr3KSLB1oMAH/vAMVz+xckyOF8pmJThE6uGqLvc3u+bJVcDIjZw4Z8vSqJV6Rs5ARsROKlUr9YDXWKBnKL52tB78JfNd//HPy+/k48XP+c931/pf/i51Oauy53DgSxcD7qjVa4N3FcF6Xwv/qc3Df/3Qcj50zXN+u57aqP49TO91icCWhrbd0cZP2JFTteSyVh+5Bn7CsdAoaARfu3UB+337Xn7wz/rp+0mBqsVyRwDPEZbsaLjr9LnWfbHH+d9CrRztPdAzXKRr0A2SN9IQPB7V31S3IyeE+JQQ4v4qr98rhKiUH3wDNaFz+VUmSqX8N/W7GQi9jk6P8BZiHDm9nxEEstpqYplEDw9lLuRe6wvsJdzFuzwGUZLGqJXupLClRk3S6wmdEgXJxb06RhOttSNOFUR51Wpb+DOq/c7XPe06cEn1FiXNQHGkm5FL+46cppoqwt/937muq8+eGXXkNErjycYLFe8b9FRI31T4Ce8pfp3Z+Rt8atoHihdV7H+zfXzNc9EFYazyEJPorai/62CI2+at58Dv3seTy+NFLRSikW/9PtxeS3vUWNbHUyM+U1yrjFbqdORCNXKB2ElsT6/tEMHUf/dnVnazpT+fGKxoj2QZV8mpoQBairLfPsWRglflrMTPXS/1jG/48w4QywD4s30Cm7x5cXcjLHhyVfonXJy6lrPMSkdwpLh9/noeW7qNb9/RSHF/MkL1Zdr2ONq4ghrrI73Sce9TTIM8mZAITxvDod6ZdqzYSeXYbgSrtg2F7quRB0rD7/td+XTucQ6lS7oCLkpgop1BTjbdOXDO2ltgqAspJeO0IFOugQDpf2p91+8eXV5zn0TV1BiIUEYu7MgF1MqwjaUCzbJc3Zls5Dd8vUvQ//zMGgZiqP7V4NtshG22dZ7d1ErOLwmCwH46zpjPhdbNNHsUzKgj1zNU/I9U+GyMWlm572X/epWDvnc/fbnSv1XsJIoPAkurvP4abl3dG2gQKipkYyKFcuTCFzuVkObXFSwVokXyKtijBtu+RiAS8V7zQfe4r2NGTuD457hOVqeyvZ5YJaeGnustEpIwmqhNOCNXmRWoViM3UuiOgjpKynPaijLlBQpiMnIxH1myHT549bN89dYFIz6feqB+m2mRAMV4zZGLNvwGWCGnA7BaTuXpiBz8C86uoeefKl5Q17kMaVlLURqiLSYDtbuxhsvvey3kNCdhIB9eTPX3JPXaGS6WueKBpbxUpRh73poebp23rnKBlJVjNiywU/2cQ8eLMZhUH8xEeJ5itEZOUd+KWP4Y3J6qlfox71+ymWMueygxWKEoReA6ag85+4cdOVHmxvT3AdjI+FBmO4rLy+/yH08krDa4m+e0vSpncYcdT+tWODEmcDFSzNPG0VgYVHEOfsX2ivdU7t8I4t6n5oQhslxvn6htL1Rk5Pz+YGV3/IaCbA26l9c/vZrjfvwwX/7by/62kWaVJ9Mbej7kMQJWejXkqs3KrKh4zja3PYvepLmehs0K/6mOXKP9x5K+hbqmYdXKwLYysRMzcip4LsuVa46OhqiVIwjbPbuym8//ZT5ru+u/rqPBVFR7lbAjN+ApPreJ4ZC+wKBs4qXMR7kmfRmfsW7jfaabB9Kplc+s6OLA790Xulf+U9CQI1dl13lreupS7B0NGnHkdgGqWWyLvH3eQINQ0UE7pJwUnviVIxeNDsVRK6fRHcomycgiOVuT128SauEa/eiqV5xhEn1kvfYKa+SUUX/uWMHBYK/8H/znUyKiMXEYTbYgLuob234g+r5RXCvdUZB+Rk4zor3xVFkjV/mZd768gYdf3coNz6xhS3/1RW1U8D46ej10auW7vYbeOl6L1I7oGCbLP71auvVyAnc5h9d1KsMhR244tibshvQldR0L4K4FG3l5Xa//XI9WJi3tP7t/KZff9xpv/9UTrO/NxV6bd/z6ST7/l5d4+LVwUEdSPSNXazgnFW2rx3EOdQj5XiBs2BY11Up9DCY5clsHCvTn6+/xo9CXK/HY0q2UbSe2FUvSd9cDCPsVriJHNmiRQFipc0ZCWwGFpXKmT53czQhocRPp80WqXnVmRTJ3ldApvqOFPs7GZB1IcNiSsnP6qyOlcMe9S7Xwyck0f7BP84OGTSJf0RA8J71sVdGtcU3qAVUPvn6b22/rlhe00oURUjXHa0GEo/I/9x/3ekqB47yMXIXC6cBGpAzXrE6IBA6q4T+VWhk3J1bU/DYwhsxQH7nAYbNw/ABn1JFTz6VdfQ6q9ROOtO2Lwn/99ilunbeeT93wYkPvG1n9o/QF6qLUSqUw3sYwc0TQQmOOsdGnmwMcbLjBheGi7Z/DhX99CSnh5ufrp/2OBZ5f1c0/Xqre7mO0YicKhhCJFPOxOD405siloEqo0X2toWZTQohpQohLhRAPCSEGhBBSCHFcwr5vE0K8KITICyHWCCG+JYSo8GKEEJ1CiN8JIbYKIYaEEA8KIfZ/vY45EigFLRsDKdxJQlQ4cvEKSsUYR84QkgNFkDxVhpsal3qfNDV/jElGrs7FSv/8KJ1xLDESusIQTX5j8CmRDFAcRhNdCUd9K4+X1H5gVBk57TMd6X5eWqO1qUUqVVEjV4k+TfTllw8tG/E51YL6ukogRzUg1dUi4wxoveYxDp8ofZ6TCz/kpMKP6j6XIimKXsbILA/6Ue5CTGa8Xlyq1SnUUwiu96I66tIHKyhxetb1yWXbalJzG6F9JBnjanFqqUWtHHbvKTsyV4SplaqPXLxq5SHfv59Dv39/w3Tws37zJB/4w7P86qHlsQGYOAMwS4Gb0t8DXPbAgGe0DGpLnR5g+HX5bVXPYZgsK73Mv17ftIvhGjKOFLwsdw6p+S53pvGiMzd0nGh2ejTQsxz1ZJFrIYlCWb3g36eNjPAzK9+omqu7+TeT35VPB6CZgt/vETxHTtHKS8MV5zcWEfSRztm6SEu31g+v13vckeTI9a9HIkNZuGjtfDX8h/pxsZ5ctetTS+zEiOkjB+GMnM8Q8GBXceTCLTaq/4j6GBtNidzL6+q/rjAy1chOBv3AyOZIDbDKyLWL4araAqeYzwPw3398lrf/6glsr4/t6w3HkZx95VNccOM8nlgW3wYGGrtnq13raPA0SQQFXOVtfQ2dwVbmxAhjRdGII/caUE37+GSgNoE5jN2ALwMzgcTcqhDiVOA2oBv4jPf4m8BPI/sZwF3Ae4ArgP8BpgAPCyHmRPYd82OOFGoyKUsT6c1U0YyclZCR04vudegF0oFohvt3iqZqqaJ0Y6FSVW8EQ8nDb5UddcshjwQj7X2mIk71GEujyo6VKyd9/WhxLQmg0ghuBNHsi6M5ciUsPzAQzcjFGfj6V782QVxlLKAWx6m4BvM8z6htF8N0RvqWLXGC+qR5EeM3Dq/JWVWpcHFQ+5ulYb9+qp8mHrAP8Pep5dC813yAX6SuoIl8KAunO3L1Lu5KKEJBX6hTplFRMxIdsvqCVZMOFMq2VBq7SqQpEcOuw12KZO/TnpFQlLUzcuAKpHQ1KCCxbItr9P7q4WXx923MJkWZBFjlBOyBHBnKnjiC7shdV67dHkCp434j9Wd/m2o1sIEJFEjzoHMgPZ6K7NnFb/lKrAqK5pSELf15bnhmTV2ZS32YjYWiXKJqZUI2F3T6/9hBd+QA31lrFoVAKVoagNColW5GOTRPjsG5jLQGPaM5cvpa72fkPGplRV/CwS04MlzfObkOhonC/6aMXHTOioo7VUMStdIKiZ1EWFCyiiMXE4hNgh5MalTsZMvAyBkwuTpbJk2mh/eb99FMPjS+KqiVWkauXixY38fiDf2s762vpnosoc9xL6xOvifGUrlVX+6SGDCT6OG5zCe5O/0VDNxygyeyn+WBzJcQNdblRhy5G4GThRDf1ZqEI4RICSG+jevI3dDA8QBeACZKKXcBqoXFfwzMA06RUl4lpbwA+AHwSSGETuc8GzgSOFdK+R0p5a+A43Dn4m+9DsccESxtMlE1cmZkAkonpPnjqJUKykEMRDNctGo3nDIgXs8aOaU+uKZGxmS0GKkjp5qUR0Vj4lDN8P1TxMCOQu8rFpeRC6I14c+Yt7aHD/zhGZ5f1XhUPmq0OzJojlvE9MdXtEYublJ7veoo1Meo6/GUVu+2i1gfEjL4ZulDHJ6/gn3zV9FPy3Y5H1UnZ5WH/SapA7KZr5eCEuHJkRYgYUh+kPoDbzOf4nzrzpDDVgpFS0c2fvXehikzPMVLZMW1HNLGYU06UMQp1I8L4QxCLDxHLmoopmKCCZSr18iNdPgJ4sdz3OF20ZT+Lih9JnQUZcDM1IycoToCU33auNxNrMHE9mlHax13TixhcUDhd8zO30AP7fzRPpUvlT7GxaVzAdUrNPkHeM9VT/PVWxfwrdsX1Twfffxtz4BeOJubdE1H9vlxVM3AkXPNFdU6pJmAWqnmO7/WvMaYGylGmulUAQ5bihD1rycidlIx3wy7YiftWl/HiaK/brXT/9QauThUu1T1ZuScCrET22elJFErqUGtzJVsfvfochZviKe06ufW6Ez/wJIttXdKwGC++hiYKbbw29RPeDb7Kb6Xuprvpf7IYUbAGtEzwwD9XkYuLeIdxKfsYL3WA5zRAKSu8Ly6a4jZF93Fx697vvqXGQH0z6lmIjaWkUt+TdlZse/THr/LfBRLOOxobKGNYcZrVGjDqT7WGnHkfgo8CnwN2CCEeFwI8TiwEfgG8DhweQPHQ0o5IKWsWlQghNgT2BP4rZRSHym/9s7/LG3b2cAG4HbtM7YCNwNnCiFS2+uYo0GoRi6BWukb2zLsuBUiz591dvMfZ/ym4uGMnC4RrnrOjYW8fL2L3w5e767tSasEMEfIV9joOXLnW3f6E/07jMf4kXVlhQBKtQXvW/9YVPU3yZe1oScrHvhRnOhHfPam+Ty2dBtnX/lU9S8SA53+Kr3/fGqvDBy5VES1Mu5bvB5r/Quru7n4H4sA6WdIl8qZvmrbVNEdijRvZDybmLDdnDiAIRk0BVdRyAGa2UqHX/9ULQigBArA7R2mU9tGkpGLQs/IpS2jMqMb2RCtm6yGUBZO3+49UcbzA/YBnFf8Au8pfj18AM/AjBq2Or23FGnOnFSHOlJj0xAi9pjRe9Wi7Pct/ELxfLppD72+VXYAcL51h78tV0d29zb7aP/xPZmLWJ79AGd7KpTrE/oYlrH4q32cL9KTEaWq9YgrtroG/K3zatNyQp8zBg5MXJsBqKQrxo21EYudVIiD2b6arKI9q1qedoZDLATQShTsyprxsRCAGaljqM4z2pKnFzdbq+aSKDOB4S4kroKujkmeeMpkeng8cwF/SX8nVC+o8J/aRy4O1eaBREfO+6sC5mXMkCNnYWssqITguVP5u+kfd9m/XuGSu1/htF88FnsO+phoNCOXi+lJWi+ueLCaZiFcYv3Bp0ECvNN8nJ212rdoj9/+SIufKO5xDvYf65m9vlyYUbGpL5jP3vSjh933Lqq/92K90BkwRhVPbqzUkmXEkUuim+sq3H9M/yjE9DCd6iJidTtyUsoSbtbtImAdcID3by0u3fBEKeXIm6UkQ/GVQq65lHKDdh76vi/Iypn3WaANmKvtN9bHHDH0huBJ1MpE1coItVJX41NSsFFFsDYtKtIiChgkF/rXg9VdQ7yyqT9RmUvg+A4RwFxvUljhTB/5h9aBkWbkeggaY3/OuoU3GS/x0/RveJf1KL9J/zS0b60Fuj+hcWnZdrjsX6/6z5Uh4sQYPmO5pEZ7PDlShhvSS0WtrK1aqa89HU2jjmfE4qzfPMWKbUO0M+QrIm6U4+mWrlE9XgwwTaOZvR7tLBS1MmXrGbkmylj+2KkmLDBVn6CxEbi1bAP5UqzYieNIfnLvq9z5snvf1BrW4YxceGcpY1oexNRqKvz1+bWc+vPHeHXTgP/+4FiVTp0yPPtp5j7nYJ529uS7pfcFbxruCt0zWQpckfoFH7PuAlwjyTecVB+5hGzGSI1jIeLfG52/dKrQYjm7Yn/VP0mhJM2qDAmFZXJG4mu1RE70bJ4eEBgN9Gs69mIn8U6dJL4+ZqSfHl169Cy9ok32eXRESzh0eJkqtZ4G1MqY9gMjPCcdUSpxvchoQlQ6ej3arcrIjff+quwIuV6QYbEUCGjAx5ovM1Ns4zDjFfbQajUVtkfLj+2F6Kk2cuoqiOlgYGu1cKZI7iPnP4/JkuifvSghE6cQckAbNFW+f3e4vVAj9+1fNRGeOBxrVmoavt96AIAbym+ueE3VyCXhWWd38l4wZZbWQih6zn0JttJYtybQg4gpI9kFaiSYEQ0k6cwUx0kWCdO3T9BqWA8ylvLLVH29jKHBhuBSypKU8jIp5f5Syhbv3wFSyh97jt72wDTv78aY1zYC0yP7Ju2Htu/2OKYPIURvtX8Q7oId8LRN1va6xqopksROqqtW9stgoc8SFgtQYyYqmd5CvubNUrIdHn51i9/gUGG4WOZNP3qYt/zssQS+s2Rl9v2syL6fVdlz2Eus8umcKyNy/2ONkTpyi53Z/uP3m/fzcTOIuB9ivOb3Q4HwjbhkY+XEHcq6aVgYmeTVzx8WBHCjR2NRf7aLWMdUukICK4OFMr99dIW/YOl1AtEobdz46GwOosQn7BHQZG1H8vjSbaNqghuF7vxsluN9esd40e9nv7bJ9sSa0bGEysilnJwfFFEZQGVgjYsYUDr011pFjmdWdnPO75/h49e9EJuR+/u89fziwWV8+oZ5dA0WakZv9YycZRgVsu9RI60c6S2o40u3vMySjf1c8+RK7/XgtXBGzn2mHFtFYwP4g306T9h7eSc3EAomnGveyxnm0z41rIiliZ2oQNTYZuRMIWINn2iWcDcjMHj6Y4yV30SETVIJ1KIoVDY5Ds84u1d9b682v3eKcLZlY1+O8697gXsWbYq+rSr0bz0WBnwS/TaakQuJPcTs3whKdjyDBQLDW28domrHlMBFMOa8Br5JA32EGKlqZaAoHJ7XVMCogyEEDp3enKLW1NJQN5LKeUg5sHo2N+rswb9f7ERKyaINfQzUUeNZNSOXcPHUfOX38JXRGjk70eYKqJUxGbkGBrDu2zdqqUTnr1p0ybHCuhgW1UBEQVcxFRRWyGn++3QaenS+1YPeTangWow1zVkP2FVbSkdKrfwf6yYWZD7KYcJ1tiXJ4kn6+Iz2YJ1lRASMqqAhR+7fBDVK4nKLee11tW/SfvqxtscxR4zAkBY4XgG9SOgjV0u1Uk9zZ0SUWulujw6YFnI1J+5bX1zPB69+jgtumhfavqE3WBDWdlc6cm8zngw9vyvzVd8AWb2dWw+YVaIt1XCXc5j/eLwY5EgzrAqo0wz0Bf/bd1TWoyzdHB81r5BMVo5cZJ9/LtzIHZ5M7nS28WbjRRq1LGaJzdyX+R+ezn4mVKD9tVsXsnLbkNaQ3kxsPxCrDaF9B32yvf7p1bz/D8/wjl8/0dB5VoOefeimjS4vIzeBfp9yuSmiprW9oAzCjBOukQPo8uh3uqJmFDrdabqmtvnk8q5IjZwLPUBw8R2LawYoQmInllFh5FaKnWhKpgmJA0VxSewj5/1VEf9oQbxOXdPP583m/PC5S70heMk7v/jxPlIaoGnGUyt1QYqdxQZfrRLi6UOvyh04s/Cdhj8/R5b1Hn1bx3XlE3nS2avqewdo9um7SrFQ4Xt3LeFfizbx8etG3mNuNEJKCqGG4IlOXQJde4ReU1SkJRXjyOn0ROXIlKPUypgaubEoOxix2ImIz8j1eQEjU0jaGPZFT9Sa2t21hZXbhkKtMSBY+3cSQWy6gpbJv59a+ejSbZz+i8c5//rwWI47q5FQKxX0ILpOrTRw/GxdWUaple5zQ8ZQUhtw5PQ5qNH+eKP53GoQOL6IUxwecvav2JYjE1L27GCQpU7AOsiT8R05PSMXXZd0zYCpHUHQZSzo3jr0Na5RSmsS9J//k9Y/yIgSP0n/2v08KROdN317c6ybUR8Sr5gQ4lghxLHR57X+jfhMkqG8g7gq8qz2uto3aT/9WNvjmD6klJ3V/kG40CqokVNEqzjVyvjoUF6GufN9MRk5XcbeolzRtLdF5GtOeFd7halPLOsKRclqqaKdaCb3OFm1nR05a4QZORuT3fLX+AZTFLrUfUhWNmatTqIxRCdudZRoBPv2+a4TZ1HmhvT3+WP6x7zNaKw27nhjvv+41a6UKtbFdtQiVdl+oHKA6FsKpeDLX/mIK167qmvsGpU2e7VKeelKiXdp1EqVkdv4ujtyOT+yr6KShvervNt8KPH9epR8Ol0hGphukKqH+jBetmWwJmVHp1amTVHZOzCyMJaqZOQU4pxHJ8apU5TSbWHSQZBRKBdD2Yksxch+lhbxDgeiKj5/pI6cELHv1X+HBzNfDL2W1LdtvgyY9bWyaTpOKvyIDxQv8p//tXws3yh/mFqxeYnh0yujDcWfXRlfl/nOXz/B0s3JGWL99x1p42od4QxweOzpj2OplSO02Yrl2hk5fa1UdeLKSPfbhyjVyoQIeqP4yDXP8fZfPVG3UmAUvmBLpL2JUjQFmC66fbVYlZHr9IJF0YycCjwdYwT0ufdGenB+wLyXM5z7R3S+Y4XL/uWKazyxLCKhEHMtRmPnV1OtVIb1cMT8K3vlB0ZMjVwj5zIa5ys6HzeSST9172QmVAdDWB4b7Eulj3GffZD/2nJnGksidHIXIpSVK5LilOIP+X7pHE7wWvssky5x7WAjKCepDDDGB4bHOiMXdqDH5phxZ6gCtpU1csQ+jsuM14tqKYuHgYc0hcqHgYeq/FOvjzVU6GhazGvTcIVI9H2T9kPbd3scc8TQC25VQ3AjmpFTqpVRsZMI5UKPHAc1cl5GjspsHLg1c7UmFZ0m977fP+M/HqiR0ncSDJNe2UK/Vou2PTBSaiW40duNhB2DVx23wbResKsHsON+w0Nn11ezFRWkAZCO7Rsoe4lVzPZEYo4yFtZ1TP+8tNs8bVdef51aOdKMnO6AjOZ3T0KLt6gqJ0oJT0zQqJWvV0ZO0QazTq4iI6dqnKqpCk7S4jiGkH7NKIQXN2VU6xHJen7ZaJ8gnfIcd5uHBHAkrNw2xK8fXhbqE6iCIkmLkHo40eP5qxpGhVBGTnMWxkWyAUM0aWIn4UBUFCOlAQohiEuQqDF8gNaDU3tX4vFm5//M3Py1vLv4zbrPYZgsTzl7+pTN25yj6n7vKs9YP9kMlXgnOhwvrunlvGvrU38bkxq5BF9QRh7rTt5oDaqoUWjqfeI8Zy2vrZVKuTlguHgnMLQFHDucVRzFeT3wyhZeWtvLvSMUbdBFgHT0amunnl1b5bhjIyNKNJH3HTqFNobJUGSOEbzncGMJHV5Gb3exhu+mruFieSW8fPOIznksoCvp1kI00FPQyhnqz8hVqlaqEopoexrl8Amvmihfsrn+6dWs3DbUkHM2mqznsbuEa2kbygQmfG6GIu/RApAP2geEmAPVSmFymrN7n3MQDgZX2W9luVcP/JizLwB7i1U0eb9rNIuuP9XPcawzcqMRmUlCNUqtI6PBLe192rOm7ZGRAz7s/StFnif9+5D3d6wx3/t7sL5RCDEdt//c/Mi+B4nKPPVhwCCwTNtvrI85YoQKblHtB8IRvKSG4BWOnJaRy0QyckgZm75tEZXGfRS6cf7yuj4+e9M8/vj4Sgo1Io1zPCM12ih3e2fjAJKYlfU6Gqu1vlG/Lr/Nb0swXXPk9Mk4bjJNkp2uoFZG/n7X+iPXrH0L7+r5HRBWQcw3WAemO3IZpzJLpjdjVoECK1rvUyN6ri+eI82ERqEbZyojp5yobq/OaBwDPrXy9c7INZMLqVYC/N0+xt9vl4RGntF+TruKtf5jPbOgvn9bJgjeLN7YT2dz5fXXs+S3aUqFjy3dRnekVjE6TMNN4iXvuvIpLvvXq1z415f87ZYnmpK4IElJloKv8hitk0jKyEUzBkMyo6nClWLP1z/vEdIATYNQrWhwPHfbrZlvhbZfVvqvGkcUFb2m6kEZiw8UL+Jjxc/zhLNP3e970XG747zVfBr9KlQz5qplx/WlbWxq5GpHn5Hh5wIVKBjZ51e2swjmIzWe8hq1UtWJK0n/wwxNPGLLkogo1IhOKYSkWulaSPstFMLja5iMr1gdcuQ0Y3tHscVX7lQZvDaRCxnrCl+2bvTeozmc8+O7Sb24poef3vdaQ85Wo2ikXUO1vpi1YMbUh4Mb3Gzx5rIhGc7I+dRKLyP3m4eX8/XbFnL8jx9uyDmr1hi6FqJ7N5JIT+oV+R3rGi5K3QS44l1dtPs2D8C9zsGx7wOY7KmhAmyLzP0A8xy35bIlHPYWqwDoz4XHT9A3V4aCjyOlJSehkUbs9V6XuL2UcKEjZej6JM2JikY9EiQ6clLKa6SUf1Jqjdrzqv9GfCbJ57EIeAX4mBBC92I+ATjA37Rtt+CKj7xdbRBCTATeBdyuBFm2xzFHg7iC2yTVygpqZUSWOEfan+Cz0Ro5oElUOnKt5GoO2Kj63e3zN/CdOxdXnXANHD/bMN+ZQ7dGB3nZGZNe6lWR1H6g3rYE+qK4Qk5jg5dt0TNyjpT88fGVnHft8/QOVw6FJEpN9Hfzf3/3buMDlkttefvQLUC4lioqclALelb0EHt+xevhZszx1Mo4I1Hfojsglta7bDRRx2FNYlnVtPgZOanETgZe94ycEjtpFgXfIFSZ8Medvf39otkmhWjPpzlGkJGbtyZ4TU3+E9vChkScQqg+9nTJ+TtfrtRpil7LKLVymydodP+SwKhT90zUefMfE2TjALZGqJV+mxS74DtgaUq0R4JIeTIVqpWJ1MoRWthJ7QdKtgxlotfLCZxZ+A5X2m+r2Hes8JKcy73OIbV31PB3rX3BHC2bW83gic7fOvRXRuoc60hy9vXthbLNup5K53Kknx69njq1UgVHy1h+LU9QI+c+1w1WDDORHjpSjDS0tYsnuBOtdQPhZ+V2Nlxxm7I0QmIUs0UgeqNq59oZ4lzz3orPOcejV07S56b++EDUO3/9JD9/YCmX3/taQ9+lEUQzrNUQnQdsu/5rpys26336TByf0ZSPUisjNXI3PBuofjZy+4xGGTW6rCbNhZv68vzqoWVs7s/zwupuPnLNc7y0trdiP4sy77Ye9p+740WE1tQNVRR1daGnK8rvqHi9n1Y2y04gqJOLqlQqWyGqtTDm1Eqd4VLDFvzkn5NLg+qFlJW0cgX9ukXLDBSq1Swq1KUGIYRoFUI8KIT4SD37NwIhxNeFEF/HdYwAPuBt+7S225eAA4F7hBDnCSF+DnwVtw+cPpvcAjwNXCuE+KYQ4pO4lE8DuDjy0dvjmCNCuOA23pFLqpGLcucLpPyi7ii10nFkaLAoWk8r+Zrc7qQUdLWo3Ayx1efuL5Uzucs+3H/tNrt+KtFIkZR5qzebrvciW+TM9huY76QtkLYj+c6di7lv8WZWbKt0sPIJjlwhEqHV/bgDRDTJK0MZuSQHIQn6Nf+M/DNzIpkiPUiQRK2UuONny0AgbhPOyOlKicEPPNLaEHAVURUCmou7qCrVyomi31e03MTrm5FrIR/UyHn3ko3pOy2ft/4W+/6oI6cbafO1RVbdt7qTvM+MjthF+ws3z68reihlpdGgOwBJh1ALXlzLAfU+vWarKyEjJ8sFFm5wHb5Q9N9DnnQwx3nUyqRvNdIF3jREqKZToWQ7zBSBUth7i19nvpwbymj/J0Bve7CfWO4/rvZ7WFWEn/T5cGyolXrIOfYh37h9ESf+5NGK9440+xXNSOitI/T6RhX4VJRoFTS42X5T6P32GGfkooc417yHVdlzWJU9J1QjG8WxxssA7BCjYKcUcpX4Vg+tEcplsE4t92qUpooe/777RumDoeOlKIcduXz1WtxHl9avqjdWiLsU0fmwnmyq2q7sLAfDVzAFLyNnKEcuHCxX85PwHLm5k4LfvKGM3CiUUaNzfdJ9e+4fn+FH97zKh695jrN+8xQPvLKFnpiAc7RdzmrP1unRmn/nZX1MoKQerht9RpMblNaVKfXvUO16jgVCjlyNff+5sE4F4Cqn6DYE13ZNuOwZ4nNCm6ldnlPXCiWlHAQaCxvWj+96/87xnn/Ye+5Xm0sp7wTeCUwArvAefw+4IHKeNnAabrPuC4AfAVuB46WUyyL7jvkxR4ogKhRMJlYFtTJetTLaKLQoUz7dMhPTfkCnVir6U4vI1Y5cJThFXVUk5md7C0ZZGqyVk7ikfA7POLtzaek9vCh3rXrcsUCS8VLvZ/6pfDJbZTt32oexRO7IK3IHAOaK9f71qJUViDbulFKycttQKNsEutiJDFFlwHXEdOO/o8GMXHOkcfCBRrgGKKNTK/32A5UZuS/d8jKHfv8BHvMWcH3M6IZxRpugR0O/0X8jJdCjsmE9MRLutXpwjRVUzUQrOb/mNKwW637nI8zFZGOozCpzpRw+XX1w/1md/mM1tHQqTMoUscbJc6t6eGmde9zT94kr6fWOiawwAso16MEQLw8fVeJSfXCGZaairkQZP6+u7/KjnHqWWaFIqtKRS7jFRpqR29yfjxUhKtmOb+SWpPm6jadGITF8YZVPWbd71FxZ1eCx6s3IjYHRFBxCJoqdJEHff6bYytHGAuqxcqOGrMqUF2QqtEYqWrq6b3edNo45k1rC66hdCtXrNPKLJH3H6Hz/nVRAXnq7Ga/um6HIJE/99uryKRWvK6dNZd56ZRslLIY9KqDaPiCbWOeN5ZOMF3wxiwftAzim8FP/eHuKVaGenBSqO3Ipc/sFOPTgQi3nKPqTN5Lp0m0vieELnJnCodlw5/GooFxZo1YOFsq0ZoPg+lCx/vUuKXNdD6LfOWkufM1Tza4lkKWzKSBQRX3B2ZXVzmQ2yPG+/ROHUkTZMw7rI6Up0zvDa0S0TZbCWLAEdOi/VSM1cmu7h/nxPa/GttmKs59V72QpqwlABVtV0iOKenrjNnInzgf2aGD/uiClFAn/Zkf2u83rWZeVUs6SUn5Lykr9Vyllj5Tyo1LKiV6fu+OllLH50e1xzJFAGc1ujZzKyCXVyFWnVvbT7E88QfsB/L+KWlmQlq9+1kqO659ew90L4trluUhb8UOlZzh+8P0idQXXpS8FXNpKGYscWd5d/GaIqpREcxwL/85IOEi91MqNTOCQwpV8uvRZAFZ4VEtLOEz1jNDnVvVUPUY0I3XNk6s4/scP883bw4IlekZuQkS6vplCKMIcfb0Woiql0TrJoEYuyMiloxk5CX970TV+L7zZrZ3S11fd2WjWHbniyDNyuhOoqFCqqDpaD1eQKdbKybweGPScycmi169BGZDxqoaVjcElk7x6AtUYWm9HoI8XNfmXysEPXbSdRMdGZX9rOTjRV3UaU5LNFN+cPrwgqXHZFRE6gUDsZFtv8HvMjakhLBn1UytHusAn0cFLtvRpP+vkxBDV6j8NrzqzAJhjbOTezJc537yjRkauiiOnzYdjIWPuOJLjjPnMy3yctw3+VTt28nvUKegf/0D6i1yf/kFd4k668X6IeIV9xAoAhiK0uIKfkXONsWwmw04TW0IB0lc2dEUUWev/TZLqj/S5LNqj87LUVaHn0+jib+lv8S3rWn/br8tvrzimysipZuCKpaDW9dke5bJHtvp1S2q+ysk0G5jAWjmFtY5LxzzdfIb/sh4JPqA07AdT4lCNrjtaCC28UKuZelSxNNz+Iv7aKWNa1ycAQoH0rHTXyRzxjtxgLs8RlzwQmj8b6ec20hq5z900j8eXbQttG238RWf8PGHvxbfL5wJu0PItxUt5c+FyBmNasChcVn43EKZ9R6GomdO9z4oGN9Q9HKXVjnVz+jC1sv73vevKp/jlQ8v4wB+eqXgt7hT9bG+1jJz3JGpv6djiUVKroRFH7lvAeUKI4xt4zxuoA4bG0w4mkvBgVoW3ORldmMLp7kGaKjJyPrVSSpo8GkeBNIOe8akECqrxgZOib12DlY7cOPp5mxlI5FebAJKyY2ORqUsyXpIcvFrYJCf4ETu9sWU15CMUrm/f4fak29wfdqbUwiJlJSWvWeT9awThnmpRmK2LsTpewGpbgNm6BKt1EY4Z3j8qtpGmxFbTIGc4vkGjZ+TOMR/gU+ZtCG1i8k/Wgy56k00FY2W4gQhlFLpIR3NEtbKHNvo152mdnPi6UeBUtkl3kAe0Mf6z8jv9x52RXl+dDPoZu6XKkdMyrLohELewFctOorGdihEkicLl64e3VWsIrqD6RYa5/uHjKmql6qWno+jRcvRailPM5yr2s410hWpl0rcZ6wW+bDt+a5G4xrf/Sfh++X2h5xelbqqaTau3p+ZY1chdkvo948Qg7xkMnJF6aJtqj4n0+cX/Jxu1FTcdRyJw+Hv6m/w18x2+mHIdyKFIgEWtn756s2FhCBEKkH79lhd58JWg31Ujv0jUqVDQA1pnxmTgzjYDB+qp7Gc4yFjKOdaD/rZozSmEWxC4zz1HzhM829ljdnTTxlI5M7Tvy3JnpDdfvuq99jHrrsoTLyTT+MdK1CoOSXTfOIcnWr5QT0ZO7eLbXl5GSQ+kZ0igVkpVR15moFDm4VcDimkjtX3hXoX1YUNvjtvmVwqlj5YSrer+lzvTeF/pa6EMdY5sRZ1gFH+yT+H9xa/wjdKHEvfZGMnIDUbYOuo7VDjmYzzPhzNytfdXY25Tv7sGrthayYiKO0NTy8hVK0mA5Po4gFfkrJrn2IjU1vuBNcD9QoiXgNeAaLWylFKOeR3d/++w9Bo5b5IwI6qBLd7CMxihLOUiaX8Q/sQT1MgFr+qTU1DrU1u1MpOQkVNZGh2zRJg73yvjOdNQxdkSgpGXvnvHGGMnsYTFFjqZSg/TqaSFxSGpRi6KICMnWSMns7umZNhCPtQ2opkCAsdfiHVkJjyM2bwmtO0q4CZ7Jm8eHqYsBJvt5WTsfyBSPRhmjndZU1iaToO8hSsLKRYVx7FDVwHKbnPPS1J/ANzM6q3OMWwbLLJ080Do6mzoy7s0k4xFVsvIRamlOhau72PRhj7eddCs2Gu1uT9wXlsiqpUgWCOn+ApY27u5vI6hyD0IQY0cwM/KZ/Fp8zYs4bi9YSRMopetdIQoskudmWASkggf0Ba3eWt6ueDGeUzTKCglO77/FritQJ5b1Z0o/w7uHRU1hvSId9KxOzylzGplHSojty0mI6eCS2pOylDkYOGWIi93pvly6I6pqVbaYUZBFI0otdWiZxk4bOjLMynlBjm21FGX8O9EgTTznTnsbwQ1chmKFVR7hWosuKT+Tf7rjuRnDyxl1ymtvHXf6TXPzZbSj7rrtbb11A+pU9nVCOa/lTKZKqx/5m5iHQca4WqH6L2qqJUqw4+ZwhQipFiYEna4tq+BZSjRkdPu6x+nflvx+mXW77jFfhNxa97Tzh7EVfNEGQjKsVMZuUkeXa5HtvG0swdlafi0yqedPf33VROxIN8HzQH7QR8f25VaqT2upWBZUabQwPWytBo5CLJtKa39QK5C7MRTdqZybSs2pLYZHxSrhge0AIOOkaq9ApxmPO1TfePqlutBkRSP11De3eRRBNUauK4nbHf6DJTIAjaa7xYH/fCiDhkiR0Kt5LM6RaElYIxQRi4hAOr91evjHrAP4ARznv98SFbaG1E04sh9UHu8v/cvCgm84cg1iEACVyRm5IIaoXCEcSAm21XpyAXZHhXlzMuUlpGrw5FL1U8z0tP0AN8vvz9x3yRnayz6eyTdfKM59gY5gamih49Zd/I2+SRfLX2E9SRH77uG6usNom5oKaHVCF+PZgohZ9sQrmhNLsahcOwWRKkDIUpglBCGe70HTIPb21QEd4A0T/rvWaqMPyHZkC3yl2wbbc0byfTfTiq1hY9Ykzk6l+OS/iu5NefK65/000f56mnhBsgX/2MRP37XfiHVyugi639fKXnrFY8DkE2ZvH3/GRX76FnL5ohqJcBaOYm9WQXAM86Ys74TETexhu9DV1FuIv2MY5B/pr/MHsZabrOP5Gb7OABsKfy+PHpGLlpT+I+XNrDPjCAaXy0j98GrKzNccYi+u56M3NFzJ3rvTcrIBTVyUaETCIwhNSe1kfNpXi/LnZnjtfaUIk7sJIFa2YAnl5StSlFmadalER1b+ClT8By5Ougs/264inKBI3egsZSnnL1i902qF+4ZKnK7FuGPo7H946UN/OIBt6729H2m1VR6kxKK0iStgpG9a6FzVp2RdXefXUUQIEzqRarDtmVFnQ/EOXLuXOdnho0UBgIQlIWFJcuVQk8NGJLRHo7+eWj39TbZzkQv6PGkvSdHmosxhJtRPMx4peK9j9rxBvJrkSybEqbojwROXcql4GW5Mwd6Qlq6Sme02X2fbKbDE4OJ1snpjur2rZELrnkt+flqglqJYifeX18x3LO7lMKpgUOnxzDojtRj684euMFoNb+MVG2zXmXUi/+xKHb7SNkJFmV+nf6F//x+56Aqe48Oit7bKYZIUa4oE0rOyI3teYSCVXWYgrYjawb/1fXT1b5NEdjd4exrZYY5o9XH3WC/OezIEV+2oaNuR07KOjQw38CIoBaVcki1Mjw5qYxMlPMfTftDoGSpnDY925PVqZXeAGmNiGHEId3ApK0i86ucKRxX/GnVfZMycmNDrUwSOxn5MdfLiRzIMnYz1rEb63jC/Cyz8/H9dgCeXtGd+JoOvUVElC/dIvIVznYr+VhHLr/uv8MbRJH3TryU9a3ddNoOKSnpo5knrRk4hSmkim18xvwHM8tlLiu+j1ktz7OocxsDlkN6/FMUgGfJ8mxTlp+MH0dL+XvgpAHJzetm0DSrgEj1IowCd3c30frk0Qw4B6CmlqRFdttgEbzv+dhrW2MduU1aRk6pzA1qgQzd2H7E2S/2c7YHeiON7HMyXbEo9cpWJop+OsUAe3jZhTPNJ3nY3h9wjSvV1LxdDGPg4GBU0E0gbBwkGYr1QsrKjF60j1wc9GBQ3L6SoB4wjlqp1EYVRbZZowrrRqW0UkHPrHLe+5z47zIWTXBPMQLn91jjZT9avLmOAvN/N+61D+ItGj31UPEKTxHvyCX5Xhf9/eXQczsmo7BsS0APLjuyZm2UIyWr5dSgj+K6Z6FzVlVjMyqmM16rA65WP+Kft5ShWlOFaNAlKlyBmcLw6PK2SGHJckWmpRE7MomBoVOm18uJTBT9XFp6Dw85+3OPeREAExjgczFKt0kZsyjlSs2HfRHVQEW51OeolU7QWif6G/20fDYXp1xKbFfXViZoCVH9+xXKNl+/bQHH7zaZE/YYW0aEPl5rCfCE6oor9q3+Xl0xHAInrV0M+7ZSVFgrWn6QMg3KjqdhMFJqZZ2DLGkei4tp1ROA0NuXAFxYOr++ExkB9HVhHAMVrAfbkXzjtoVc9/Tq0PZG5vmy7TD3a/+kNWOx4OKTY4NOjVI1G9k/GgRS7w8dIrSGun/1jFxfJBDjsu6qM9Qa72L6BsYcvtiETFEWapKI1Mj5GYmod145UJVzd4SxmG9a1/JXxy1EdWRwnGEyvkxstI4nDo1EJasZdFEkZ+Tq/rgqx47froudGKKxiE+ckt1pxtPc7Rwe2naksZCjjYX8XKuXqgsSmiJiJOPpr3C2m0W+PgtDpnlrr8lRA1tY6sxgF2M9g3KIvQuXAoJW+vhY9noAflLYhT2GB7lk8GaubJ3BremdeLu9mJwpeaDFzTgZVjBWNpd6sHSfJtXP35b+DfgbrbtmkdLi96/tzbLS/pjCZMvwFu5ffT89hR5A0LaH+wXuzZkcfVMrh0w5hGNnHsvczrnMaJvBtoEcGHmEsOlJD/G3bAuPm5vIWtcjzGF+Lh0WOdPYQjureJwmqw8j1YtTGodAglEAJ4NT6kSYQ0glnyxTOIXJyHI7dm4WTmEqjXR6ikZo47LiPZ6zF1VmfI/Xr2mb7AhN2O0M0UtbbLG8rjhYsp2GjIUoJJXR33Afufj3+YpiCdRKKfGzDHFiJ8qAznrMAp0q3KvV+nT3D1PAc+zsAjhO4tzTyM+Q5ETsbaz0H08WPb4j978hI3e7cxS7ldfyca+2KUn1DFxj83ePLmf2hBZO3isw4u9dHKZSxY0tffwNF206mqpHwhxJSFJ/cNWL/H3goIp64Tioy9SmjY90giy3ez7u/WI7MnYdS8rI+TBMDO+0bBHfeqURJAWudMq0LwpEe6hP18esOzlcb0zuYQudscfcqPe+I6jrjJYyqPlKr8PRW1gMR4LDG+QEBmWWVpHn2VdWc2rQGjPU2Py5VT08t6qH659ew6pLT489xyQ8t6qbr/59AZ87cVdO37eSOqvb3/qYjLuL9frsqNNXy2wJHLkwtXISQXa3m/iMnBKt0YPOpQYCbUlz6UgQ52zUE/TbyytN6JGtHFD4LSPveFgbeqPwSaKvQo1xsFCucOKgMQr9JXe/4h9r/tpeDtihMiBXq+ay2v5JUIeJmzskyQqlai3W782+SKC4SO22D3U7ckIIG/iAlDI2/SCEeDdwg5R16JC+gRD01gJqQolm5Fq8jEw9fFlVj3Kw8RoHG6/RUXaAd4ZUK3Nk/PYDSkUvipfW9vL2Xz3Bew+d1dBEoxaq7hiDLop/R0ZOdx4NIRqKuMQ5cr9O/4LZ+bAjd0P6EsCNgjrOmTUFVtQpONIJ6jc8TBD9FUZadJ9qUPVlr8kZ7MJ6WkWedoYYJhsykkpYDNHErLLNh7tLLCydwA8ybhH+VtNgrZXiAvFutqQMZLmFnWdtYu3gasp9++GUO7FSg+wyZwmr+lchzDwCeKX/aV556em4b6w9sukr9HH/mvu5f839ob3adnP/XoiJ2ylkjT+tlYB/kgJypAgyC0YqTLEyqVwcdDjlNnDSyHIL0mlyHUApAANpN+MUpoAUCLOAdNIU7GaesZs5tDiMIF6xstczns637gxtV4baNtkRcmA6xSC9so3+GEdu4fogOxFtojoSRIf7fZ4xf6zxEuNsk9vZu+I9QUYufhF02w8k18hVZOS08avTYntpDWdNyvkx6SOXtO++nrohwC5iPZ0ezfV/gyNnY/KD8vuYJrp5m/kUHVVEkFZuG/KNnBWXnObPR5YhQo58nOqiXvO6bMsgB+1YPVvpSOmzQQDmv/AU38wdCbgOnolT0Z7C71PoXW3d0deFni6ybuR86w4uKn2Um+w3c+xlD1EsOxTKDhPMSjXfqCBIpSOXwlQZuSqKvUm4bd56nlnZzbfO2JNsymTVtsom52HIINAp20PZs1ixEZLX0TIWa5xJfo85tTb1RkVQPEdkrZzEfrjjXRcgizq7m+U4BmimlTzl4d7Qa3H9F8HNhFgNUF0+cf0LbBss8qkbXuT0fSudQL12qZYAjz5ko/d50jvV3KU3BNf/6v30KjNy3jgRNiBDTmeSamn8OQSP6+0/Zxoidi6L25Z0rXR8IXULgNcjd/s5ceAqqhekRUaUmSG2sigsTJ9YX9qIfZbRhNaSbMiQGE4dh44LAv5r4Sb+tXAj3zpjL8a1pP1xloqpm4yqVjoxHny1jFwc6y6KRjJyta7y9h0F/x9Db8is86+bNPqcyshE+exxiF74wxxXLl4iA/U/mfWNFV2AQUrpL6rv/I1bR3Xjs0HheT2Y5tXIba5HNnUMauGSUI8iptFgSm5DJAoah7lafcdnrb+TK/+epnT1+IYyYNKU/NohhWjNIVT2hqsGleHTI2B7Gav5beonLJcBpbFA2hfPaRIF/zoCTLIdJtkFJhbmsk7OBeCgXXfg1ZcDYRVhCv7+9u/z7ut/w4KNG8HJMHen5Wwe7MUQJvvNnMi+Ew5l09YJ/HXeq8hyC0iL0/Ybz5v2TPHoukd5fvPzDBTjldLG2zaFwlR6y1NxihMxUj0IM4csNyNlGmk3IUvjMDKbQVo4pfZgH7sJYQ0i7WaEUcBoWocwhzGsQQzL+7x0koDNgootH2Uis4sldisWkeUsqfwTSLsZOzcLWZpQVeAHXLqUbsQpWti2wfpqKkcKKeMXxuls49r0D8EByzifvznHhl5P6vHjw3EY72fiOypeVjVyrmqu9I3zgkzxspzDrU1n8Y59JvDQo/uzp9DEepxS4oc24sglGUq7aaIa+2jZuf90sRMdKuNSb1uSXMmmJRO/9MeNDX3fexZtqunISSlDztCOtns9TWz+mb6I8WKA4wo/oTeS6XDf6/7VA1ftGmXyfOsOAP7Huomb7Dd7FG0XcTVy+vwG8dRK4bjrQSlBxKJaIOFzf5kPwG5TWvngUTuxeGPlOehopuB/NzdzXXv9q9bP8KTij7g6dRl50n7NXE/kd1Xj45LS+9hDrOEeJ9wSOKqEvUmOp182M010kyqFgwNJWZ5VXUPMnVx5PZOwLUbtWsea7sAhrkWt1Knh9dbNqnGmAuZK7MSWBohAKEYKM9QjFAKFS8DtPqfZMEnOSOw5aCOrXmfl7ANn8pfnK+2xz988n2s+eCg7TAjOVc+exkHg+Orb9TgLo4XEYIHcmYPFaxxivMq9kXGYlLFvhAm504RgTU2yLfW1IG5o6TWP0f0Vzr/+BXdf0+DH79rPP8lYaqWTLHbiUyuFUpgXDERs/AKpmomUsaRW7gAka9W+gUQob7xA2s/IHWe+xHzjY7y3+HVeknP8yX+4joxcXoZTsUM08ZW/v8yNz67lEitQYlKGfavI00KOIZrYOlBgcrv7GTuOb2bFtsaaTwPs4jkya+ro65XkbI1FgWtSLYd+g9fbU06hqsKXhxONcBuHvz3zGu8/proYh7q5m2UQiR6QTbSJnE9Z09FaL7WSIAuiUxu+Y11Du8hxgAhU3vKkQwb3OFF5O2dF0f/cKI1ESkgZKSaJIyn1uFkesfkEuje65//R4w7nvVep7Nx+/vvWrO/k7DOP4uxdzwagv9jPyt7VnHXV3TilTpqkzT9T32BGucw7CuezSc6p74vXhMTIrsNqWY50UgirHyPdg1McB9IC4SCsAczsOoRRwimOdzONqV4Ma4BV6RSr0inAJssd/lGdUic/GZ6IVWzhhOFh2mMG88tyZ4bJ+KIQHWKo4nruJDbSRIHFkcjlaL9z3MKoK81enr6Sv+Wjjpz3bmVok8coBWO1jSFfEU+nVorUNhCSfMk1FAwhyVDyAxFKhffato+w5+ETObT4U5ZtWMUFTCQrJeLJbyHkjlgdA5iZjSA8cqiT5r6Ni1hSMLClTUemg75ckZntkzlqxuHM7pgdfGMp6S0MYGQ2YrUtxEj1IqxBLKuHd6baKdHBjHKZk4eGmVFuxga6MitJp19CiDLSbvIovhJEGWH1Icud2LmZCKOIdNI4hWkgyiBNhJHHyGwFUQJhu/vYWcAAJ4VTnIid25HGuv/oUBfQHZ+bhGu81OvIFcsOLZ7tHlUEjBsbrZnAcD1sp/GVO0TgOOEI8xTRDUim0s3OXm+zs81H+b1dmYlRH687U+O9eUhnD4yPoVG2iMrgVjSzWpmRs/ya6bKiVor6xE70oMvmAffxrlOqOzMTNGdTlR5cWX5rReZeoSjNWOq2QoE055S+HtqW1JZgAxM5oXh5xTGiGbltdPjOS8YOrwGFBOdgFGzvmijXUNW1qxjmtcVOEqiVXnC7nBkHubCNEFI4pYwhAke4lsJm0rmN1t5ZsXWI/776WR764nH+tlqK2Xrz95+VzxrdCdSJ553dONh4LRQ0U0hyPBvJyOnMp6TsaJLwiH+MiGJ6tYDh8q2D3nFcROcO9f7EkoQItTJPumKOejJBwEpHVUdOCPF24O3apo8JIU6M2XU8cCLweM1PfAMVyHpOWl6rkQPIiDIXWn/l/NLn/W3R9gMAvyifyQXWbfy67DbajkpQl5wgq9YkKjNy4GblVsomPnXDi/z1/CNxHMme09sbduQm0OdLib/o7FJz/yRqpb54RiMk9SJJVUv/yEYpnMvkDJY4s0hT5pflM/lp+jfeKxIVXY3KFT/z9OO+I5eUAJQSVncNkdXq47pkO20iF2oqrSSklSGsZ1CToIQldK7/LkZlM+aCyPrNT5soMC6GqqXX7+liJCY20oHzr3uBnBZZW6mNn/Ouje8HtaE3x8ptQ5Rsh12ntNGebmfn9t0pD7iR/E62soM3QfZE+OOjg8DJz6KYr92nJYqvtv6IjR2r2GhZrJJTWWOlMVLdCMPGSPUy2NHLN5nApc44diyVyZcm8dbianYol0lJyVNFC8t8kSdkO0cXe0ItCAD2F8u4LfNNAD5W/HxF9HKkSFoTx0ecgOlsYwNB0EItprbop33GjXS0LOLm+QabU5/i6B2Oo0UO0W8Instm2ZZZSbbtYcz0VozMNqQUbOjZh1vtFvoMg0zT4wzaW7k13cIG0UKaf7E+u5H33LmcsixDCzykjNe1DwDQFKN6/8AmYFPMl3kOkGna0x10ZLNsGd5CwS7QsnPlrt2eUfaKmeaVTDBvGtxWo3PS6CAdC2k3Yed2xClMQTpZnMJkhDWIkd6Kkd6KmXGDIU7ZvW+FcMAcxkhvQwiJlAIhJH8G/u7MRMg8TbnfYw/tgl2YglOa4NaKmjmXNlwaD4hQVuWt+07jzpc3+s/j5iad2lYvFUl3utLCppNBn7YKyTLn6vh602yVkYu2yZnB1pBisJqbnnd25WDDbW0RleiPc+RUYC/oD1Zfy5iBfPAd716wkZP2nFIzIzNBi3WrgMft9lEhR+7Mwnf8ez96/vWgIiMXk/kMvR6hbtqYfjuVTDnsyCV9v2rKkaNFbWplcvYksSG4olaKcB+5oEau1z12tjL7rDePj2Zvq9Uvb+nPc9Nza3nHATOYNb55RHVxSY40hNdaSM5wKSgBMYBXnMbXwJFgvcdocksMApsJkh3PWo7c6q4hHlu6jbMOnBmy7ZLGjX68WFsscmWqmZ6tHlshmLeC72ArynaEBRPXizVI5qQq2krZmMhRip3sT9B2QALHev+iGASeBD5d43hvIAahjFykxHB/Y1mIMhLla4OrMrVxyvH8fX2HfxwdunyzLnayVSuiniJ6WCmn8dyqHr59xyJunbee8c2Np9sP9eSTCzLFAhljOUWQVDum37sZy6BcpR9ZEpI4+7qD1yizs4TFqcVLMXE41gjqsnYSm/x+R2/RlPAAWu3g+lmmEbsY/nPhJi7860vsqkWVu2hnNptDUdxtdDCVHj/6XE+Pk7iMXBQ2BkUsv/FnVpQqjHsI1+Y9ttSlZQgcbk9/gwmin1MW/dAX0YHwAh+nyAjQnrV4+y8fpz9f5omL3syMzqZQZFM3APvkWDpyI4eRn8q3yvMA+KzzAV4pHgw4GJlNmC3LMJtWY7W+yrBRZkkmDZk+rgiJFvyLJuAC2mizWzBKD5EtLkeW20CmeSe3c5VoJ2cIjrJ/z8P2oEsNLbe59E1pgZ11jfp0t1vTJ1MIc8jPJILEKUwGIRHmIIY1yHeefpCnF8xAmDMwMpvAKGLndmS8V9y/1TTYaFnsmn6QLWJnjHQXZvNK5tHNETc45Ke7zn0vBvNNmP/Sr/j5S78iNW0cbzFmMGAawL9C5dlCSIbGv8w3lYgJ9zIPmOc9z/Cwa6JLmJCZysD6HTk7dT95Q1Da4wwe37KYnuJm7PxUt5ZRWiANpk8oM7NjPC2pFp5avZJCCS9bOgiiSH9pK/2RkkKn1IGdmwXSYOcCfIoHEcDLmQz3tDRTFJCSgm2iGWl7zo85CNJC2s2obKBp5RHZ1S5l1ygizHzkc9rdTJ5wwMkijBwYJUC4GUGjjDAGMFILgYXVx1pmW+x2oVGwc149sNW6DKt1Wez+ANJO8/lHb2a/KXvSmemkC0lq/Gr3+5VbWNw3yIq+Q5jdPhtDeFmKUMajDvPTKfvZWYWpoickgBKtAffPzzNWdLGvrEc7imbcpopu1muN29U894KzC/fZB/HZE+Yy/965ofdUOHJmyl+DFLWysv1A7KmG6llXdw3zzl8/ySXvqN5LS83lOZn2yyZekbO4zz6QXcR63lK81FdQBPhR+d1VjxeHqI0QZzPoeFlbpy8ofgogyMiVw8G8REduBOtzNQgR/O61xJ3sKuMzabRGM79B+wH3t1c2l52tzEDbEUdO//xqAeeP/Ol5Fqzv48Zn1/DUV04YUX+0uxcEkatJ9PBc1r1eRxd+xrqI01/N6YNwHWo9EvdjAV3cZzK9IQp7Uk1frTnnTT96GIBrn1rFx48N2DpJ4yZ0iWKOHd1U7fObIyUzOqVc0XUVtdLA4bepn3L48mUw+Dy0TvaPHajJh9l0t9iuu+VmjJPvg6qOnJTy28C3AYQQDvD+JLGTNzByBGnVlD+hKLSIAu81H/Sfb41RsJIYnHTSqdx4zfP+ccKvB5a+iloO4zbe7ZatjBeD3JT+HkucHTi1eClXP7EKgN7hxoUVVCR0npyb2JxWRxK1Ub950pbB0AgWilSCk6irsI2sQk9gY7LY2dHfMo4BVuI6clMiNW3NmiOXMgRx1QH3L3Ej1M2RjBwEaoAFmaJPtjBV9Pj7lWwH00iuvxM4Pi13gGbyMuUbRjrypBGIUIP5nYUbqb+pfBxHGIvZ0dgSS1+aSD97G6sAlzL1R/vUxPOJw+b+gu/kzV/T6zlywaTV4dGo7Bj++L8LZV3K21D9nAycwnScwnQ3NGMO0dn+DMLIMZzOMb5pCSmrn34y2GYZ6aQRRtF1fswBUtmgR9CPIjVaGe4Zk/Oe3wvZmODrPbbJA2ImQ75A0Is0EVCEy8CgN2wsx+B9A70sS6VY0jaObjtPKdVDSZu77NwMSv374xQnYjatIt3+Mmaqm7nFEhstiwHTYHK5TBmLbbQwgUP42glvpd3Zlwt+9wBfyf7VPdB+n+GeTa18/M9PQ6S+6eOH7stb95vGqT9/jJ4uFV12MLLrEdYAwhzm62fsyHdv24ostyPLrchyO4rSuL/5AKen3PedNjTMRd097m/k7MyZxYsBt+1KvACIoUW8HYz0NrdGU5qAACcYp60ZKxTEEKlujMxmDKsfs3kFRqoHzDxGeitIy1VSLU50nXBMzOw6pJNxa0oBuzANnDTCzOGUxjFXrOV/mn5PzhB8JXUCsmUVwuoPOXr+Z5tFFnbPY2H3vOC7aMrxf13r/mtJtTCpaRJzO+eSG5pMekI3GAVe6s4xfdvu7DVhr0QmgOFUBmymi20hpkJUldlHTEZOrY9RgadJoi9kqetCXr+1z+AzR50C94bvm2g9GEaKniH3+P0lAUaMI5fgDgzECBPVcjoUTVRXdJYYnFf6Ymi/dxS+zY5iM/9yDq16vDhUUCtrZOQcDGbnb6CZvC9Co3rRZez6auRq0fgefW0rf3luLV89fY+GFanLNahwuhhFVJgikVoZqZEL2g+4c0O7Jy4X58iVQtRKm0Kd/tiC9a4dsLHPY9PU9zYffblSaC76lHW7//jW9Lc4pPCb0P61MnJBnbJVlzLiWEBnaY0TA6G6/eSMXH3Hfm3zYMipTqJWRimtizb0MaOziU4vcRH9uGrUSpUsUE55KuTIqYycK3ayl1jDSeYLYANL/gGHfDRQu/QYRyXp2hW/L5/K2eajXF1+C6BYXslquo3UyO0ExLeVfwOjgp6R0/nXCkrNypYiNInoSJvB9uhipddOqMbiqtZuixzn1xvsYazh2GklHt048pv6AMNtHDvfqa+OKYnaKOvYpxashFSVqalZ1lKTrIbNmrHdKnL+SUflY1vLvfzqoWXc8dKGummQjhR+JFWJSORI+/UMimZUS/ChSXMbh2WGIbJkY+S8C6QRIjx2pnnS+Vvp9CN2rVSqsuk9wTrqaGURhW7kNnv1OHrkV1E8+2ipoB1sb+iRYZ0W+5yzK6rjzkYxNfa92C309rzZfxoQ2CSIIsgMlzb/AFpW8hB78LC5I0aqj3bRz0xrNY6ATtthg2WxTnTi5KdjNq0JZX+kNFxKntf4XdrNIErIcitIC7NlBU6pA1nqQDoZjFQvRnaDT80DgRAOBdOmoP22piMo2W04pfE4+Wns3L4nXzxpH774l4VcOHQX7/cascvdP8KLe57MF/56Ke+0n+H9fQMcnb+CnNOJCpPYg3tQ3PoW9hYr+FvmG5SBYUPQ7kiec3blXcVvsPdO4zll9hEs2tAX6nd1zaOv8ZOXrQonDtwF8oElW1jdpY9JA0ejyr5z7slcPHhv7OWZLFzHrUe2Mk4bt8u0RstJt2u4kN7AKSZT4KLzkCyNxy6NxwZKvYcFL4giSIPoslwrnDZEhhO92tofF45ntZwKOIhUj1fbOQEj3YVIdSNEmbceNkSBLrrz3bzatYJSMYuUKQxrENMs4mAzVBpiqDTEqv5VAGS8r3ftioe4dgXMaJ3BwVMOpj3Tzm7jduPNO7yZtrTnMDglJLDJNOlwHJqkZJbYyioZ3CdqHYoiqDUJjLokRy4qbqLo5sPeHBbX+zTaYw0rw3Ax6OMKldTKJGegd7gyJDdUrN66YCLJyq465sldmCdrlybEnldk/XHqnDN1JVEVMMtW1MjFG8ddQ9XFS87947MAbB0o0Nlc3b6I9rr84+MreeTVrVx48q6x+yf1Y5tIH0Y5F/OOysyvHcnI+cduqnTkyqGMXJncCJtxV2R+HFnVHumLBNY/aAXzWnvMury2u3Kbjha/N3Ft3YWxQi+tfnnIJNHHq9pvkFgj10BZje70P7W8i+N3q5yX9STB0yu6+JbXZF210Ihm4KraWDL0J0StzIgy55gPYDuu9HaI4ZTvDx1bzTlFb+7/XvkDfK/8geTPjaARR87ArYO7I+5FIcQZwAIp5aoGjvl/Hia2T0MpyBQlkXxJ3AxX7b5rUZWlmWIbxxnzeNg5wFfHUxP1Rjme3QlUkHYpLOFR9h3JVyFD0Zfz1iXFqyHJ2dJvppEqWyZRK9PaZ45ONVOwVXYwSfSFapyiGbl0qZcf3fNqXUds1jKmSrI940Vr8qT99hMqM1arfkA3fobJMCyzTIgRMcmRQSBCPYWmeIbugGyiy3MqJ8Uow+ntKyoi3g0i410zPZqm+kNFZbW3F3TnTWemZyzTp4o+4BzID0rvZZmcjtOUhtg8a+IngDI2Sx28c2AQs9zEPV7PwdOMR7k8/UzoHXPyP/SMDNul6EnD7Y3nZEPZn7o+3RzAyGzBzk8HBGZmI+c23cjhLGdm2WanUoknyvtxXul//Pe0N4/nhB2OQOQdZtt/QdkyIt/HQVMOYueuo/msdA2LohOnxidY6InUWOALwCgVQXUfNqXMkCN3y3Mr6E+gaNuOpLuGAblgXbKK4GRv3D7n7MbJ5gv+9mec3f3H9Sjf1kLdc0yMs1oP9OzOBPpZzVTAQJYmBLIohalQcB2p9889goNnuwbqR//0PPcvD+rVvn/m3hy9J7y4+UV6Cj0s713Ow6ufpnfIQUoLK7sZiWT94HrWD2p1tk9As9VMa7qVLY7NUTvM9Gi2MLlcpnl4AeXiJs5tncyQMNin8Bon2D/gkeG34JTGk/ccm6gsPASBzigbIDoXBXOnO0fGiV2p2i8fqSZ2npTmkaXFGGqlAziJmZOuGOXF4UL1zJSiVtbTmmek0JkwS0ZY+6R+p3SUWpmQ5bj6iZWcfdDM2Nd0vLy+t2qmaFNfviKr+c+FLp1wz+ntsU61vgYqw3im2MKD6Qtx7pgOu7wEEdZKZUbOCP1VcGIycjobIyXKVRvdV0f4fWVHkq4yryRlhoFQuw+FC//6UtVPb/VbWr1+LBcbk41yArPEVuaIDTxOQEVOplY2cHztWvzu0RV89bRKO1S3LdXYApeKmrHMhqiV6pqoXdIRsZNLUn/gun5XViTkbBdde1E5noqBEJfIqQeNOHLfB2aR4MgBFwJrgHNHdCb/ByGlDHnwZcJGTBTFKq/pmZ6KxQq4PHUlBxV+60cF1EISbSq6f2k+jNCRmy02+U7pImd2Xe9JzMhp985Ina1EaqWWkRttv7p+2cwk0ecXDpvYvoGoIv3jGhBz9aPKZCtEU/Iy7RspPrWyhtyyniHrky2xYjng1Y4IyGuOmMrUDtDsN6WNc+Smeg4fkJgxrhdqItYXc/X7RSPNtaA7ZI3AEMI/D73PYNoytJo/wW/tMwCYNIoxpHrGdGh1gLsbrsiLUi0FN3raTytgguP+xrKc4ivWDQgDLimfQzWi8FnGo5xtPsrXyh9mhT0dezigW9m5nXhT2eQ4M4ctBaaQ7CR08kUQIZdShlVUF94Cp17qG7+OFBXGkI7flM/gE1awhKiaJXVLNqXDc2C0p5cO25E1MwFbBpLbdChluqi8+4P2Af7jpLmnkXljLHpiVkOeDEMyQ4souFmqGmNez6pE63QksGP7juzYHtDGf1Nezg//5dY+/+w9+7H3jnkeWPMAC7ctZLA0yIJtCyjYBYbLwwyXhyEDA9oY2GJZ0L4N2MY6b/55LZMG+mga9xcA7uqFF26ZSmv5eIQ5hxdbijyW7WDIMBjEJF38FwPlXlaULWaVyqSAmZrSKgRZviGZJW0aCCE4au4EnlgWtBXJRej+i8r93N33aVp3G+ArJWhlGoPOIprK/ZhNa8Aocu+Wo7AWHECT1URXrotlvcvIWlmWbOyhaVYXqPoVUeaOdTuRGp9FGAWXHluciNsKpQOc5oBauR0dOYD77QM40ZzH78uNNepWUHXO2Si1MoH+Nr2zPmfAXXvj16y+XInDf/BA4ntfWN0Tuz0sXuE+Ps14xu3zNrgWcj3QEr7HA0cu3EeuwpGLych1yTY/qzRHbGCzU9nQvOIcY7yR6CZHSoYK5cTWIHq2SeBUlEnMEevrEj9TaKSlRAJyywAAyM1JREFUlY4GOzZV4FU5k1lsZbYIK1UlZeQaqSW0q1Cbe4eL3LtoM8Na1lynzvcOl5jSXmm/VMvI+eui9zyu/UDL8HpgemiNpzAQOnbqdXTkjgZ+V+X1e4GPjegs/o9ioFAOXfgSZkWxo45qr+n3bpxc8SvODoD0owLKKL7JPp53mw9hevUUU5x4NbF6oG7MIZnxDf9aqEf+P23FG4Z7Tmtn8cZ+zn/THK58ZHnF60kZOT0LmKSaWS/Ub61+1yn0+M7sAmcnjjUXhGhbtaBu9gHZFKpXAzdD9rx00/QqS1WLWtmqZeQGaK5oxKuQJ4Og0tABN8umREbaI+qKQKhNQbpOxbckqO+jUyuVwb21wSbNphCUR+DJmUJge1OzPjwzCeNwNGNIUb06YhT9XnB25TjTjarOFRt4UYapRQeIZXzco13/wz6ChYniQpLL01cC8HF5J18uu9P0PmIFxxvzudI+w68vWiWnMkds9AMAe4sV3Jn5Orf3nwUcgSPDEuoMuca0Jd15zA02hX+PS9+5Dz+7fymb+vMVLUnUnKYaALsZuWAxS4tyomNiO5JfPLA04Tu7WNMVT62CoH/mFjmOVc4UZhubKUsj1AcvaXpqpG1Joy1ORoKNcgJzxQZmiHhhFB26CEL0p40zmsqacSQQzB03l7njAhGRLcNbmL9lPqZhMlgY5Ht/f5CPp//OHsUiw3I8m9MDXN80ix5LclRpK9PKZdZYFnlD8Ey2BenNl5uGNgE30rorXAGgXYcMD7MceDvTyTgOc0oljh9+iZ03r2WFdLNOLVoQTK0ZV527P5+9+RnuW9QFMuMHx8rAje1t/H7jvQzbOYSArWnYSgoYxiJgUCwdfpSfv/ho7G9pRWJL3awM1RwGv6tAlsbzB6eXu+RkttjdZIq345TGBy0p8jPBGRua2ydLn2PP8mpeqkNwLA4DUlErw/N9UkZu1ynBD/HKpn7+8txaPnbszkzrCDsJcePrj4+v5INHzmbR+uTsORAywHWEe365f0PBpnxfjCMXpVZ6NXIRsTkn21nxeTmyvCJ3YG+xin3FSh5xDqjYJ4q4rE500/fuWsyfn1nD1R88hONiKIGhNZG+ilr3uWID+ZJTs2etgqJWJgV3txdUC6foXJWUqdVNnDte2sA1T67ih2ftE9u3MEpQKpYdnlvVzQE7dPK1Wxdy14KNodf1LGfZkbHjs2pGTgtwQqWKKYBju+M2ZDsVw/abolaONBDeiCM3mXixZ4UtQMwU9gaSsO/F99Kpy5Vi+sWOcSjIZEfOEIKrzj2YC2+ez2v5gOLwmL03x5gLEUhayPtOhpqoX5ZzOKTwGz5s/ZNPW7eTdupvNB3FTp4j59Zo1Ge8JHHCd5/axkseLWpNAtf7hvMO4/lVPRy766RYRy6p/YBueI+2IXm/l/1s9wxxvXn3YjmbY1ngR2GrIUWZEpa/AG2jI0RzBNgsx7HRU31SzbprFdcrA92RIkTNjCIvvRq5GNH1Aik/c9QZ45S2aZSBuIhUI1ATm/69JvuOXEfcWxLRaLN3BX1ICK2nTCaV1M5iDDJyIWquG3leLHfkOFxH7ihjIS/aYUdub60Xz2nmsywsxxttOvX13dbDfLl8HpPo446M23/qEOMVXwRpK53MYaMfALjT2+ftw38D+3cgbcbHZJhTHrU0jjXwnkN34NcPu/dnd0RBTxXZq58wmzKRGJSkSUrYVcdTPQqKP73/tcTX1D20WXby5uLlHG0sYF6kZUpSNm00tbXbA1tkJ3PZUFcvOZ3CpAyQfcVyjjfmY5Z3qti/lmrl5ObJHD/rRJZs7OfwHVr5ae9WPpq5BoClRhMn5TdQ6N6RFXIa30/9keXONL9Fzbml9/Oo3JszD8nQOeUF/rb0bwCYUrJXocgE2yYvDJ5IT8Cw3HukYBgszmRYnMkwIXstqf5jsId35IlmwauZDpaXX8VIb+YLD9/D4+sfJ2fnaNsd7MJkVhSa+aHs5JmmLEvTabBzpI0sA5vexDvMx9lVrONZZ1cetty2EELY7LrDNlpbchTsAo502G38bqSMNH+btxKnOA5hesECJ4uRXYeR6kWWWzGymxCGe18IIRHpLtYAa8gC/aR5quK3dIoTsId3dPsMijJKot3tV5hFltrBKCJL43zRm7i1tkiK+XJuxfZ6oTJyzc6ga616N2iSOqW+DL3lZ48BsGh9Pzeff0RovzjRsu/cuZiuoQJHzanVozX+notTrdSpueR6K96j3qGoleUEaqVMxWerFjqz2dtYxd7GSmQdscs4+mXUabj+aZeJ8YnrX2TJd99Ssb+eSZ8ugizzOjmRmWIbZ5hP0Z8v1e3IjZRaKUZKdfGgGBD6d4D62g985sZ5AHzqz/O45/OVAvp2hKF0yd1LuObJVRyzy0RfZVtHtPF3nLlQzcSKLv1xDJKpAwuAHSIZuWiNnCd2MsLW3o28qxeopmAxlzcagjcMXb2rVJNaWc2Rg5P2nMK9n38Th//gAY4vXI5AcqLxAseYC2kVOb9oHMIFrt20+/VHGTlyR05l5FbK+v35pGzGl07ZnVvnreeEPSbzyT+/GLtPZ3OaE/dM/qykhuB6pi6pRq9e9Ecycio7NSQzvtPVGdOPTSFLgVeyHwLgs8VP+gb1kMz6rQAU5ss5vuOopIO7h4rMHJfcMFZvN1HNuS54qpUOBo4UGJriXZ50kDmKycipPogQ3xCzEaiJVa97UBQqXWq8HozU1tYdM/0QceIJMLoxpO473UFWwYBlTtA8LS7LvosIapQ+af2Dh+39eFZW1gTMiCyYJxgvMkds8J8fYy4k7wWJlLPcJIpcl7okfKC+NXTIAT97D0Cbe45qIUqao9SCFWUVqMCV+s0zloEQ7oKWorojZzuSuZNbWbalcYGdLAU/QLBWTsbB4FFnv4r99Gya3s+ykSxbtdqWsUK3VyenjwlwKVhnGE8zT85hrTcvf+LPL3LYTuP5+Jt29g2Xf2S+AcAf7hnm4p5vcPHbgia0ekPmJKPme3cu5k9Preb9h+8QEgsZFq6RmKEYEvXql820i2GaJOA0MSG1E9848gxeWzGH5zc/yzVD93Gkxg757+J/85vMj3ktneK65pmsyeZ5JWvR1TRAtuluAP7Hb2/htnO4b3X4HM3MFgYycL1WU3jW+P05eOeL+PR1qzg29RKnmwOky+O4p3y2v8+pB+/Gp44PnKLrnl7NN25bCISdlChmiM3c1XQhBWlymvUJ+i2HT6X+imnk+Sf7stJqxshs9tqF9CGExEh3YaS7SHXGr3lROOUWnPxMnOJ4hJlDOilkuQ1Z7sApTkSYw2AUwc5i56cjy53UE2RVgV6LMpTz4Dk0SUrWUkpueWEdE1oDRsezq7pj943Drx5aXocjF5+c1x055TDpfQwZ7oq+xXMOpB/YDlQrw06QMOPns4VyJ+Bh9jRWx75ecd4xJ540KyRRDHVHR9XhD8gmN4soXCd06eZBzvrNk7x135jGmxEcYrxa9Tx0zBrfxNpu1+YwBKPi3Wzwynn2NlaRpkSRFFPpIlNshZhAclzwaFVXfH/jZ1eGx9w1T64CiHXiIKpgOfKMnELceqXmzFAANO8mKdTcanniTuUqiZxqaORdjwHnCSF+LqUMZeaEEFOBjwLx/IM3kAhdZrmMWbUOrjq1Unh/3eeqp9kASwA3axKmcYY/R2ViRuPI7WS4w0JXJ4tDyCBKsLY7mlJc/l+uYXXgDp28uKa34fPRa+F06A7eaGlP/ZEaJ0Wj7KU1UJ2skpE71wyUpy6wbuVpZ0/ApQcNR4RDemSbrx6paBFXPLiMq849OPH4es0d4DYIjoGF7Y+dy8rv5qLUTf5rW2WH78DpPd0UdBXM0WbkHEfy9Iou3vO7p/1ts5QjR+2FXsdIr60+JHWnLmPFRzpHQ61UDc7dOkBJCpspnoOxifF+c+O2GFWyPSJGxM2Z7zI7X9kdpjkiEjFddHGIEc5UKZqOTl89xoz0NxvuZpzsDduBtht4SMkyiOQ6XrUYRluSKCqJ+gmFEGStgF4ZHU9ZCnwvdTV/t4+m7Ow2IicOwoqHmyKtHnTo9SamNm81cslHU09SL3YXbjT/FPP5kMzlD62r+C/rEQZllr0Lf/S3P7Oym2dWdnPsrpNCPd3eb97Pbk9+gPcfvoNPXaqnj9yfnnLH4vVPr2FPLZiT8x25UqjpbcEbJ+mIJuc4sRfFreOZlf4nenLkT+kfgYT9C0U2DE9ksxzH59se4TctM3kxm8VI9WNJyexSidXODCRTOWn3mUxvnc6GDTvz9wULMDKb6bA2sUd2Hlkp+URPHwcc9A5eaJ0OrPJFLKI97qLGnevE1cYTmc975WAO+w5leMjZn09kriQjyrxQPJzFOiXPKGBm12Nk12M1r8DIbkA6GVfFVDjgpN2ekWYep9yMYbnzgWENYbTWJ6QFIO0mnMIkMIo4pfHI4njAwM7tgJ2bgbCGQZTpcor0GYIOR0K+j4dWDHDvos3c+Oya2OO+uKaH3z66ou7ziEOtLHfSdB5qT+BdK71uW9G/dUgZztqVZXxGThgxNpcosdBrPTRTbGMc/fRowYE4xJVANJrU0jNyAZtgHHc7h3KBcRtTRTdf/cdC1vXkYhlKURxouP0mjzdfipXGNQ3hn3d7NgWezSFqNKeuBb0m+XPW31gpp/Kj1O/Aht25uiKAHfc7JbGt7l8ycmH9oYJdM1CQhLiG4Apl77XJ+pjc+lro2Mq+GinNtVGxkzOAeUKIy4H53vb9cYVOWoFLYt/5BhJhaTLLZayQg7XE2YHdxFo/O1JPjVx0rhv0ImutIhfKlkQpnMppaNL6mDWCT5j/4DCvGfi6GpmTtNbgO4mWpm++4pwDeesvHuP43Sbz93nrY/ePQ1KmJMnBGwkUBUXxnzsIFBaVke5m5FyKTBT7GcGEO8fY6DdnHdbqORR6ZSuDHjVS9YB55LWtbOrLM7UjfgIIBADcY+k1cnfYh3OG6TpMRSz/7KKiIivlNN/w7WCQVobZS6zmGbk7IEJZukxNsfTqKDsy5MQ1k/edx82iwYzcGNDf9HGYVKs5GjGLXs/Zz4gye4nV3JX5qv/aZjnOj4wr0ROFDMUKZwzcJrFbI45J9J4+wlgc2+wdatQhDnfTKiOOU9nNxiqDPIka7mfkIvRwNd/pDpNlCopSGfphR+4i60bONh/lZON5ri2fkXyuNdCmNcNVwZg46JdWv85mA1nYrQMjm1MbwatyJnPZULH9v6xHAHe+sCiHFPfANXz12o2VXhBO75GmZ8frER7QjZlhL/CUFmW/IbjryLkOfVRtT2Uv0zEqfAo9so1Bmjgyl4fBNOeULmJqajkPWBfTIiXHFr6MHDeby97ktv748bZXKfe7gYE0W7k2q/WWs7I0pcLZmGrtB5Zurpd0FP6dZoqttJHzFYi7ojRxJ4M9vDP28M6Uuo9JOKYDwgaZcpVn09sQ6W1Yra8grEFkcSIYJe+1LoxUP9IxkXYrwhxym9CbOcxm1xkzs8mVMt3A0cxiv3yBYxdczWWPlJDlNjBmuuqq0kD3tF/Z+O8jYw3kg7Gypd+916bpLISYjJwkPE5tX+wkom5ppjCyazBSfZhNq7DaF2Ck+lhWauO3g+18qLefncVGXqghXhNLrUxwhpJuMV1oRtES18uJvmDddLr8rFkt6AmEa8onx+6j14rra99oS37XanXSn7T+EXrtLcZz3OYcHdoWFzxKYluNBqf94jHOf1NAOjzTeJx3mI9jDv4OvV43DupaxjGSDNud90JreK4bpPSDEOp66uKDp+w1hVXbhnm1jjmnbkdOSjlfCHE2cDVwGcFMJYBtwLuklM/Xe7w34EI3VE7cawavLQ7oJAM08Q/nCM40nwRqUStVRi48wFWbgXZyoc+KZuRUPVYzjWfk2hniy1oGJ6qEGUXaMvzePUkCEvrXmNHZxPNfPwnTEA05csnUyrGbBFSNk6KVKqejV7b69UApYdNGLpYet6cIZ1WymrETdeQ2MMFXmFKUyWLZ4fAfPMDyS06LdShaIhm5n5bP5hTzecrS4POlT9It2zjTfILL5Tn+e/SGsj2ylSGafMMjI8r8MnUFx5kv8b3S+/i9fTpzjeCajNaRi0a/9CjWNlF9XEUx0tq1pObzSWPVHEVgoFfra6U7cQCb5Hh/zEQzcqcY8VPtFNHDVhl25JojjtwpxnO+WuQCZzb7eM3cAZbJKpScXE9FtoLSEEiJJUteRi5+jlKLcbRnka9aqV0qyxCU7KgUvAvVO6ldDPP7B16GGs2Ok9CqOXLV+iiJyHkpjLWAiR79Hgn+WD6V0023V1eWQkVUG1whpvVUBkP02o28d/2eWdnNATu44yhEXatekguEDeSccH/bUEZOptzMrah01H0Z7yqZ/a10+AED1xE0aCk302K6b87JDM06PVq7VBU1wFaGrFf7qoQuTI9uN1NsxaKMJKhNPemn9ZGOJhAOlJxqPMtjTiC1vq3Bel8XhudAgbTbsHNtkNuJct8hMftKhNWPtJu8thY2RmYrRmYDRmYbOCYi1YeR6kUYeYzseoRROe+9lM3w0tIbaIpMC1IayNI4pDSR5VYc2Uqm2IpTmIq0m93Xyx105boYHyPhH4eKGilRQhh5pDQRZp6C0xn7vqufWMVFp+5OxjLpz5doZZhdRdBSSSkEhs8/nJFTmbiy5pyutiwuX3sTLTvNq3i/SA3wy3Gd/LWtFdH7HGzbGapoGPTnYtbFOm/3vlyJgXwplJFT9PtNcrxvb00R3ZTsMlRRDf6AeS+7inVcawfO2+/t02L3NQx8DqWeARutrsDWKkJ4SuhLh5p+dNGlpIzcaKFnMn+W/jUApVtPg4tWJr0FqD5vCSemD6ZdhFLOn1tVXfwmbe2+/L/25+zfPFnXeTdEyJRS3imE2AF4C25NHMBrwL1SyvpCAW8gBD2bMW3qVBYtCi5JTma4xz7Ed+Sqi524f6P3mGpFkBGl0ECKUqDUAlcrI9fGMMNkQpGrC62bQ/tsqOHI6TdhNpVEVwvfqCPJeiRNOCnt2KNlPSlHYwfDpW8EUvktPrUS3GaQ0bYQnQywkxGeuHbwZN9LWBWqlT2yzS9MbhYFDBy/2Wt/rsS4lkrFyeZQjRy8InfgsPwv6aGNMhbfKn+Ib5U/RFPK9H9jPSujqKK60IhSUvx66s/83j7dp3VBuF5uJIj2BZuiCXV0GfUZBApjrUcxY1wTxMzno4kOVuuNN0STP2ZUewsFnVY5J38dy7Nu89BWka8Y1ErwRrXDMIWkhUClch+vuTdUZtO/XDqPT5q3s6OxBcp5TBlZqKQDhf6axdpqwRqKSF0rGfZwRs6gVHYNfb0xNECvbPGDJU0UtdHRGFShf06mK7JUOoSWRe/XslSNZnvPPmgmt7ywjr1ntLNwfWU2tDlthrJgjWIzwb0xWfSyRk4hOhAmir6KOlNHytAapLJRl/7zFT86rQsP1SMwY2gGsk/Zp+jPRTkyvsOvsnTq11SHr0bRfsbZgz3FKiAIfOnBimEytGrjaY9pQbYkH1XltTL+GqQychY2WQrcnv46E8QA1+RuA3ZpSAY9KuRwpLmYieWAzts9wgBE/RDIsu4smjiFqW4/wdjdSxiZzchSB9JJY6S7+WPTN7i/Nct9LVMYtC2ENYDwnFwhHETa+44Zd82K64J43M1XMKlpEk2zxiHtJqRMIUudbobQHEKYwwgzj7SbuHLxP8lMzSGsQYQ5hNm0BqHV4947COm5BqlyK05hGnZultdLM8PvXuzlxDkHImUHM8Q2UsLGwXNpSnFiaUHrp6ezGTZMvpsm0lxND8864+k2TR5pboKewIlzChMp9e+PPbwjqY75ZDueZ7NlwcSFtHSuxB7cFac8DmHksXOzKPfvjxrZZ/7qiZgzSEbfcImO5hRSSg6/5AFyJZtzj9jRf10Z/pvp9O2ttLCZwADbYrJHpxjP8tv0z/znbzGfA6AgLV9FMoq0afhKknp9+FjEsN5a+J4vpKVjXEwZilo77tWSHFu2M8tBZymk8rVrPdW1jKNWCsd14its61w3ZScDSHYSrviTnq10tdrqm3MarqzzHLZbG33fGwhDXR4VDZVmGtvMhhysAZpC0eJq1Eo/IxfZrjeL3dVY5z+OFvUqamVa2LEUHIC9xCruynyVtc4kTiz+iAJpdhdr+G/rPn+fB+39WSpnJJ4nhCeFREn37ZA6V9BpUXq0Wa/dqxe6AdHKsG9k9slWttLp9+WaKbZ6ap4B4mrn9vIM9CJWhWrlgGwOcahbyfnUzsFCOdaRU46V3qhbN/oUJNI3WpdrWZmLSh8FCEmy62hjmBYR/AYjpeYqbBsMv18tWF2yDWmkiCXzJ2As+nelTIMvnTKXVduGeNv+0/n7i5UZ4dF8Tj/xtL5VjitMEW1vcYrxHHsYq/1ebPOcudiYDMosrSIfW0vX5Bm7m+U4JEF/QKCiHUDUsVzhTKOgCv7LhUpHDmD+DZrYSXVHbiCikKZEdCoychXNmV1IbYZrEoURR2LafOnt6optY9F+AOCHZ+3Lx47dmdVdw5x3bWU2VXfkRiK22qUFjSbQz6et23xapcKkmB5ztiNDGbmOmBpYnVpZj2Fhah+S1zJyynkekE0UhDumKjJyisoVuc9VnzyAZ53dmWO6NNI4Ry5HJnTdTt17Kl89bXdunbeBVzdGUoqm7si5a5GFzRTRwwRvfp7V+yxwfCgjUgtxbSCUomi/bKqoFd2eqGs8yRSOpnbtFKaxDybH5buZIT7BD9fuBeYQRtr9XkaqG8PqR0oLI92FaeWQxhBGZiPCKIGw3b/A1txWrNbKOrUoFvUvJZ1crgp4DmSq362J1GoDf7fkYX63BKZm5zA83ebE5ulsNU3mlEqw9UHKt56BLW1SRorz9j0PKTMYOKyyLC6YMomCsR4LNyvxmlZaMDHVyfoNB1Pc9mb0TJc9vAt/7n+Eh9sd/tTR4dYqdoYzd6W2ReQ3vBtkim0xzeOr3UuLNvZx5JyJ2I70e5de+1QQvJuC58jJ8aGAcYcYjM32fsa6LfRc9YNdLaf4weAoMikTvDlJD1aOhWXmisVUIs4mUgGU5oga5+f/Mj+24fdYINqjMgnRhuBxASjhuNtaIrXqDHdjO1OYRB/t3ty4VAb3oEDUvQ407MgJIWYDJ+K2GvizlHKVECINTAU2SSlHF5L/Pwa1YEkzg2kYoYh2n2yloGVl6mkWGKVWrpJT2SjHM010807DlQUuS6PCSdApJ00UGYgZGlekfgHALGMrZ5hP8Xf7GP6Vuch//R2FbzNP7lLxvih05y05I7f9HDn90LojlzINyk5jeky/tN/Ou62HAXehfrPhTuY9tFLCYq2czGyxmTliA0+wT+i97ZrRrVTcFMqYFTSgfppDfd5ayIccuThkNaW4apBaCV8frXy99CFmiG3cYrsSvyUsumVryAkAONF4IfS8idHd/lFHepLnyG2R4+oaE7oycr2NUaPYbUqbz0t3HOkr1j21vLLWAkY3Vh0Mvl76EN9LXe1v+0X5TK4ovxMIt7c4zXiaX6d/EXr/nfZhgOsQtZKnQwxh4PBM5pNMEv0cnP+Nb+TmSdMt2yOOXFj1NUoz3CAnBAEku4DhaW0XpOXX+9C5IynccZDkyKlrEj2+chz1zJepOXKVhn6A7CjGmu5UVEPSlW2E2nPQjuMwDcGuU9pY1xPfSkWvQTENgRNtiFQDObLkZJomUWSy6K1w4iAIioTeV3KYqM1DurJaX65ER1MqdE++vK6PWjC9LKojhT/vpEWZJs80cDNyHjUy4rBJ6SptpiOZ2GEytFDgyvIZ2Fq/VVVj16JlWB2MsPKsEHzs2DkMFmyWbIxkQ03Ld8pV8NLCDlFvhRe8GEqYY+MQ58jt7VGYR0arHDlGMp7ADRxOEANBLzm7BSfnrjdObsfQvpXUYImwBjhqd5NnNryA1bYY7CxSpjAzG3FKE3BKHS7108mCkWfuNFjZs8ltni5TlIfmIsttCCOPU+rEsAZJZfpxUutJj38ShI09tDNmdoMr0gJsyi+Hduj3ruWydBrsQegP5ryvPPYVxIQDEK0G7xg3jbIQCDtDofdQjjTns6Ktl17D4Jz+AT586h845A/xRv34UooLezaztvs07mrpwGxag5HqASRm03pS7Qsxm1ZT7DqOUt9BLi1WplCzir9OWd6YlCYYOZBpv4F4fGBZatTKcX4wDOIVsgWOP/aiuN0+KnY7hAPuSfXhI4dggxzPdBHOdo2PUJK/av2ZfZ+9Efa8pkJs7NZ560fFYqiGWZojl2+dVVOCJAhAlSkC3YZFys4yQQxiVMvI2ZN9BVIIs9kaMV8acuSEED8EvgCYuGvqU8AqIAssBr4O/KyRY/6fhe/BewuWmcY0RMgQ2iI7q2bhdKiFq9KmFLzkzGGa2c0+Xt+pHlqRkSiM7kDGRRUMHHY2guLoH6d+y732QaF95tXZtyZVR0ZuLLIpSdAXeV1aO2UK4qjs1aDTEK9M/dQXF1G1c8vldGazOST3rqDTEBc5sznCXOw/L0krlEUDNzuj02tbRM4fR0kTml5zVw1RKZbr7ZMq9tkqOyscubeaT4eeN4nRZeSiffGCps2ddY0JvQn4SOuY9LcNaMZb0uePdqz+xT4+5MjdbB/v349KeGZ/Y0WFEwfwD28h7pWtzBBddDLIHLGBSV70//nsJ7i6fArgZt0LIhUSxVgbodr1R+o4tzDON8YHBgd96sggTWSU0W+lg4xcgtiJMkfKWH6WGoL7RGdSW9o8WC0jNypHznNeamfkgs/bd2aH78hkE3oKxkF39JvT8b+PTvc2DUEpxvBOmfHbFbpoZybb+LJ1Y+zrs0SloluuWA5l4ZpFgSby5Mh6jcNToTnylhfW8eN37Zd4DhDUHtkYgagJRf965Un781hU1ERSKTYCQQa16AUz816AUx1TZaJVBjvuloy9TYWB8H56PSMXEibw5pPhhNrZOCjKveo3BvBR022T0FVD4bAWkuopdUbJpLaML7JjaL0wG4GaC9Kl2mILlecjkOV2tm1ro9R9LKXuyp5fUfSVmsj1Jlfo2KWJmEWDor0vxa7jAQlOE2Bz92ePomiu5QePX82WjQv4QPE15hZLLEunMKfuS/aA/8YwDK5ddC2r+lchW+YhW8BBYEpJy7q30T98ECdbG3hXzyIKQtAiJV1W8rqZ88z7CWVBqfuYUEgiPeFh0pPuw0gNkJ16B9mpLoNCtYc445Y/s3RtJ007bMBqqVSY/MSTl9D8bDOHTT0Ss2UmstzhOrXmMC2yQL/lsMZIscocxjEX86dMJ7uXcnSU+ip6A6j+vgAP2fu5KpUebrKPT/x+uvO2PWrSdCfuSXtPjjQXh+yLd5sP8THrLlgLvHIndvroimPcv6Sypm4soNfmG+V6dSPKrG7bzFsmTWerZWE5gjmlVt7bNwzIilp18n04UvoBtpxMh9ZfNyg9xtRKIcTHgS8BvwDuBHzddCllvxDiH7iqlj+r95hvQFMPMi2EECGxgA1MCHH6q9mLyg4QMTHkLZ6zoRanuOyM7kBGaS0QlslXaNEG5k9LZ1Fv0j1lheth4jCWypJR6GepL0AjiTrp12cPIyiwVjSgdR7/fGpMNFwv/o8aNCWsUPYNXKNXL8Zu1WoeBwvxHqiKWFfUhsSgVgZrq+xgN9aFth1rvBx6Xq1nXj2IGgRqkttKZ12ZL91oacTY1pHssMXvP9pFLlpXtlkreO6pUkMHQeF4j9aPrj3S6+9DlqvSlyNT4WhtjgijRO9hx0j5Rvfw8JDf99LGpGxksZw8ODYppVqZmJELrqveh261lxGsqJFLkKfXBQpGQ61UGbnBBprhXnTq7qzYOsTRcyfyub/Mr/t9euBofAz9GcJU8qQARJKDpzAgm0EQCrg9bO/HFtnJf1mPxAoJvLZ5kBPN8HiZIPpZJ7N0DRaZ3JZtmG6uO3IlLfMWOHIprUbOvb7qK0sZv/6o9hhK5CTvO4ju9rZIhjWuPjq2Zjrd6m+3tRo5PSOXst3HjThyat5a7OzIZjmOE8x5NHmBuwrFyghqCd9YSY6cGThy0zuyviNnGWJEhPek+txGUGyAjtpIDSJOFpCY2NiYpM00e07enzdPuIC1L1zBh1MuQ+DYXB6mjYPd3w3A6Tudzu3Lb+eSR/6CIQc5kNW8c2CQH+ZmAe6YtQBLBQMT+siBLhBX+eu6Wbj9yUy+G6t9YVBbaJQQ6W5WDXWTqlHyPVwe5qF199O8Q+VrJ6DKV+6iCfgx7UA71uQ7yA4tpTy4G+WBvcBpYn/hthkYkE3c4xziO3L9srlqUEEPsif1UK0booAwC8hyKzpFdWXK4rlslr8ZbTxqjmObUSRTup1Oo4+B9At8TEwiJwycRb/Cyd5N08xepLRAWmAU3CwmDka6GyFKSJlCmDmQBk65HRwL6WSQThPCKyBBmuBkcErjAIl00uBkMNJbQUikk+LV9GJ+aHQybBgMGwb2w1+gaYdlmE3rkHYzpb4DQJqsl+O5delanutdTMvcf/FoqhflVpUNyauZNL/v3Eq2azjUmxcAu0RZylCwWl9/DZHULKoSjWTkPgncKqX8nBCx8nEvA59u4Hj/p6EuUFrRk8w0pnDlZF91ZjJF9PCYvU9InlkvIo/CX6Ri1qpoYXWcaIouG54S5QoD6b/MSqpOqxa1vME+IfHcogil7F8HZckodKNRN4xGZpDHn+fzjqt0tsUzlNXNqkNFfTKiRFqGjZd+mkOtAiBQIFUZjYYyclWEcgCQtVP5cUXUSoxiqTODXYz1YdnnESBqqAYyyxPqknzXlbaSsh8jRZJ4zmhVvACWOLPYw1jLFtkZcoairSCSoGi4WYocaCyN3WeYTIXjotdXKCiq5/XlE0ibhp/NzYqSH2YqYeII7zztEmlZvSF40oK02WuVoP+CliEY8tpstEQyvHoWbjQ03mo1cjo914xk095/uEspa8ToDLWwSJhjzEhGLnafGuNsDyPc4+t2+0g+W/o0HzfdbMAOMRk5IETpBphIP+uYzKk/f4wPHL5jSC0uikUb+vjbC+G6UUNz5LqL7vfKUPIdmbxMazVyypHz5U6qKt+qe0M5cmo8KNqSMq7jHbmYA06Yg1FUQj2eaiVOyJFLl93gVCOqopM9GZ4tdLJRjucEgvqprhpS9brse+zrCePDDX46FfuMtA2Lyg40OyMPzjVSV1jPeQbZYcl1qR+wu7GGUws/9NVU8yWnUnm7FFzL5lQz7939vfzgpvF0FNZzdebzAFwi4xuCdzRn2G1KG0u3DFTUK/ktm2IEvtKU+AL/5IVNu3LfpndiZrzgijmMYQ1gZDZjNq1GltspDeyJk58FoogstyOsAd57xDgO3jnNtYv+zNLepb4jGIWUAmk3M1kOsS0FZbNEqn0BqfYFwC1IO8vCosHXyuPplh1syG1knp3GQTBQrFSw1ec+PbCtP5aUEVY/RnobVmoIhwLCGgQESIGRXe8+RrqCNWYeYbrXxCm3uN/RHOJAsQslS83vG1ns2alpnmIYeEyfm3ObILcJqwGNICNdf0P6KJYAS3Qnd/V9WB6DVRh9ZCY+7G6W8M0n/+p+XgqEhOOHh+kYnsDCbIalbb2sS5fJTL6Hm2QrK1IpOh2Hg/N5DrVL2EhNuCYcVBVQd6CyEUtnV+A3VV7fCg127H0DFdRKG5Mzit9HICmQZpIMMjlmlauqpsC4uXB9RJUoPiMXGGDRupQpdLNnpPkwBMXbQEXNHYQnBR31pOy3b42cRq0cA0nby0tnc2HqFv/5V0of4XFnb8CVBwaYGWNEnWfe5T++wT6BHxh/8J+7tNo0zzi7c5jxCn8svwV1lYfI0k4ulJHb3B+f/s9odKZqkCHSWjx0AZwn7L04ylzkP3/G2Z1djPW0ixytDDNddHFv5ssMyixvKf6wZm9B/zMiRqPeL6ceqqR+bUeakdMNts+fGEiPJzlsYzFWf11+Ox+07uErnriMQtTR+mTxgliKZUEzbJMcnD7ZUpExi3NkrrdP4llnd1bLKWSbDAplTezEc97K0sQxTNdpdsp1ZOSCxy85O7OfsYJtsh01pvXf1jSEL+rT6tdvST5s/svPzEB8JLweTKLHz1LGff8QPVe7tvpVbiRHpQ+bVELWXxcTGCsK75dL5wGBoI3ryEVJ1NAeyaJP0ERRrnu6ct7XcfovHq/Ypui3NgZ9RRPSbsAyKxXNO+2vN3HtB+py5DxqZUrYmNgh2iaEqboKSYwDPyPnGfOWsENByrQ9xBUPLOXy+yr7NiZBj7JHe5NtlNVTMaYhKuhxOpJiCPr4sOoIDNSCysilSqNx5OrPYtbj9KmpeQo9HGO6jdlPN5/mrgUHM60zS75sV1JzY6hxUkb7yLm/V1T4QwiD6z96GD3DRU6OtJ6opvR9pvk453uCVLPzN2DnZmufVR2y3Mn09G68Y5e5HDXlVA695D5X4TPVj3TSnCae48L0TfTbnZw5/DPA4Hup77Nbeglfyx7OI9kOrNbX3OyfmWdjE/yDVveT2xdwLkp0TdLqfMttH1GYgl2YiiFTlIvjEeYQvdk8mamujfdKcQLpSUNu0/rmVbQaI6tNM6whsFwGgLrLnXILmWI7+4uVTLZt7jZ2ZQe6Oba0mbwQNEtJ+4TdeLpjX55Y1gu4dYWy3AYYCKOAU5joZt3MIZxSJ8IoIKwBQGBYAyBKgAAhEUYeN4vXA14iRRiucqp0mjDSW+i0BQcU+2mWkiYpeXni21i0oYBdmIbV+ipW6ys4xQm0ZVO0NRdxSq1s6Mry/r5hvl5+hPvsHZnUO4uj7Ye5urMdZ8KzfD8kMtfBGatvY/ep+/hBo/6IqrkhBA4ltzUITtU1pxFHLg8JEmsudoQRq0H/n4WqARFm2l9odKdK7wdkVsnIqffGLVZRRy4fEzUPUyuDm7SFHM9kg0TrcmcacwxXKlXvlVPRnwcVk6lEWita7WyOj+A3uvgs/s4pPL2ii6aUxXuverrqvsNFrdntKKmVAFfY7+Dt5pPMNTbwmeKnucM50n/tVU+FaJLoZyJ9flbLosyuWv81lYHwn3uG7PnFz3Gq+Ry3aUXJPbKNdpELOdKX3P0KHzt2DlH49M1aNXKyNrVSj3Q+4uwbcuTucQ7h/TwAuD1uPmndDrhy+D9L/YqzixdXPbaCfj1MbKbiRtU2yIl118gpRIuj64XtSOZ/8yRWbhti/1mdwbGTIuFjkD2+wzmSO4pHVmzvjjhy9zkH+4//bgc1A8qAbRKBzPvD9n4sk9P5qPVPwM0O63WZBWklZtBeky7VqFloY6dcIIUShtAyck7Zn8cKSY6cNhNcVT6dD1j38bXSh/1tUdXKQW9RU0pfhxtL+GbqutAxW0RyPU01nKup7MbJRRuazJ9+XrqzWa8sNITp7om9LY3RO3LHFS7n4cyFgBtYUWuHoq+2iRwT6K9QoI0qVU5IaBZfLwzvWtuY/rqSpaiNkYCuW9kQPLztNWdGaJ5UWTN9PstS9Me1cvCqUSvnOXM5wFjGcGYSzQSOtt5+QG8YX871NeTEAUzyHLmtsrNCACi6HkdR6zonNZJOGkP6nFirzlKHXyNXHrkj1wi1spF9dTEZB8EvHljKgnW9zJ7YQke0KXOpcp6QJPWRi6wZhsmktgyT2irtm2rUykNEoKiZ1NdRh0WZHcVmTzFaUCg7LNnYT2vGAgyk3Ya03bVgJ7PAzqLMPKcTRVPspYWJtsPRfc3c0/UBt31D80pMUeD8lt+zNpVihZzC6oyknAqupzCKiHQ3Rrobq20JgH9n9YCvIrq8CJnIsJVSgNOMtNNIu5ndp3aweXCA/SbvxoOvbsJI9VIe3AOnMBlptyCdDGbTSoxUP3ZhEkgL6WSxB3clxTB/zH4cgJcLZ3CB9TdONoPfsNTexPQdvsCDj4eVQbcPJPdlPsM0rYZv/3VHUPAyhuW+YA0+as8pXPWug91Az8uvsYN1NVjuPFWSFp/q7eW+5k7WpR0MKTkwX2CjlWJ9yuSO3sXc2XUeR4xPc3AhTX44mCeEOcQDa+6nZ/x3aZnU49JIq6ARR+5Z4B3A5dEXhBBZ4ANAZbOMN5AAdzLVa+TiJnC9TspMSK+D1kcu5rXhiJNQrFEjpwsMvMV4LrTfl0of5++ZiwEvckugFFZ5TiLW4AnRKROzHI05Vc1pizfvPoWF6/v8bUnG1l9f0Now6I7ciHngghOLP459Zamc6VMh9zBW85izL1CpahalUapr1kN7BW11E+PZkS1MrYPGGDVwklAZp6/EX+zjOc18ln7ZFOp3Ai6VtCRNUsJmjtjAicaL/mu7iHBd3enG00wRPfzRPpUzjcf5WfrXLHZ25LTiD0JiJ1PowfLG/AY5ITHzpRf5hxo4j8LB6mxOc8AO4d8sOSO3/eo5t0Sap5aw+Gzxk+xmrONH5f/ytw9JZVTkafGMhiEyPObsy0dxHbnNjGOS7PXfU0voA1yntugZ3f2DA1jeMl/GRArP6NEcuWIChVe/Fe90juDO4hGh1/Xf1jIN/9yUiMUh4pWKY37C/Acpylxrn1Lze+iYSDBHqKCVLtHuiq1Unpd++Z36bc7Q+zJm7b6ZSeOsloG/Sk7jM8VPc7DxKt8rf0DbHrQ9mS02VdRoqUbiCvrvE8X4ljT5ko3tSFoy8eaDXiOnO0fKaS5rDt44BpglNiPYGXApq3pGbrmczq7ojlyYWgmq/i5cCxwXlFI/3yeLn+WT1u1MOuo83kLwe+tiJ6063TSmoXQ1ZCjS4b0/TrCsliNXK15VT0YuiVrZiPCJyshl7ca+v45iPR3k1b4NOHJ6qYK6hx96dSvv7WhiYlSsLTYjJ0OOnBqndtSOEcH9+v137M137lhMZ3OKzf0Fv89rc1RWnnBmbxyDbKziyGUo8mr2gwB8t/Q+/mCfznVPreIXDywNBRIVdMVKhT6vRlr1fZV2C+WBvdlPvMrni+79/F+FT9DMeO5u+gIpCb8VR/Er8xjX6Wt9DcNTzxQp9/gd5mx6hspIabLn9FY29Q8hy23skD2Y55am3IxUpolBr6zjTx88mbasO9ZnPxiwjUK/Sz6+NVUfLRSlSVrYTBJ9TPRsy2GZoVkUWLRiLZ9+5fVw4kAgQ04cuArhvVV6P6o7Su+nWsIiI+HbGy2+JN/GreJnjHccthqd3Nta5mfjJ5M3B3lyAjzJVITcTIv9XZAGRmqALzwCdQjVA9VawFfiR8ARQojrgH29bVOFEKcADwMzgXhr9g1UwK+R8xY3YaZjqWM6nS0u66UQqFZWHmOQqCMXUyMXI3ZiYnN5+kp/+5sLP/ajuxBMpkkGYVKCRzdaugYL3P+FY/n66XtwzC7BAjdSI1ynRyZFHj96zE7+41D7AUs3pkb08RUokPb7sl1s/YnPW7cAkl1EYJwsdnasoKbGUVUVFDVnrtjAZ8y/+80k45DxDZxaGTlZs0buEWdf/rv4ZU4rXkqPNql1y1ZyZH2O9zvMJ9zG1B46xLBP8TzCWMSv0r/gm6nrWJU9h5+lfw3AnsZqptAd6lk1XXN2N8gJyQ3ezXga0VjTc7eXamV1CJ609wTgspJbsH+7czSXld8TUp5VjbZbyPuGRY5siK6xWXaGAkNKBOm35dOBoGdg6NOF8A3RBas2h4xx28vIXXrXgprUyjq+pg/TEP4YV3Vd0Vo5gB2MrXwn9SfmaPdS9Y9waGU4lJVU41Kfk6KtAPz3645cI8IMGnShJx36fDeaWsw7nCP5VvlDoeswTNY3+g43ltQ8RpJUObjG9kk/fYRjLnsoseWJMmbKmKF+gJYIxo6iAh9vvsQj6S8wZciNvkuCawKV1OI4Ry6rKWKq48arVrobNzKBb5Q/TG/HnqHtSWInZh2qdXPEek4znkbg+Nk4cAMxUUGh0Wfk4mElOG+6XdHInKgyck1OZW/BetFIjVwjNExdVbBdyygXSnZllj0xI1dJraxgrhiBJf2+w3Zk4bdP4dS9pwGBamUctVLP7O1Z5X4COMQIMk/fSP0ZgJ5hdz6dv7a3Yn9VU7VJo+iqWuqOCE36Q9a//MfPyj1YL6dQtNtolpLrht9PeWAfSr2Hk193LsOrPs3wqk8ztPSbDC39JnsbXyK39sPk1/03/73zd3nyg3/hqY/+npnpI9zG8jIVWntH2u4HQGL4bKVJotcPJq30glBx/VG3F8bFCLZF64ij8PvIeXOc68i5Y6DNsWnJT2S8F/1zRJb39Q9yzrbDKfUewMSiO6dJ4VJPjVQQOCkP7sLQyk8jneoNEOp25KSU9wOfAM4G7vc2XwfcDewHnCelfKre4zUKIcThQogHhBCDQog+IcRtQohKLpm779uEEC8KIfJCiDVCiG8JISosDCFEpxDid0KIrUKIISHEg0KI/UdzzLrhtx8IxE6S7oPFjltgf4NMjjz7DcFjjjEUETgoisrsTBkTR7pvVoPxBC2rMt+Zwwo5PeRgqKhFkrJe0o2tZ122DBSYO7mNjx6zM01aT7mRSsfr1CUpJZM9SsQXTw5qnU7eM4hQT+8IbhDddxwLAQuFBV7zyznGRj5r/Z03GS+H1Cc/U/p0Rda0mtOusmGnmc9yYeoWHspcyIEz46NFUQNndBA84uzHOjkpRPlTx17ruOf1FtPN4urjQkmf35j+fuLRjzfnhzKkqj5um2wnTyZxPCXVF5kjzJQ1qlq5Pes5Ab5Q+gQXFD/FVfbpifsMeuOnVeT8a56TaRbJ2bzg7MIj9r486eztGx8AS6Q7r1xafi9HF37OTfabK45raNTKNKWQI+d40er+oVzNhuC13B4jYmwuk27kdiexCYsyLSTTKHV57Wr4tvUnFmY/yjvMgDiiaIb6NU8KDMQpAtcDfdwm1eHqjmGSgzSagMFWLwv3pdTNgCYyEkPXPy2SodMxWCiztjtH91CRB1+JF0/p9LIC/bI5lJHzo9XSDBnMhpAcuukGQKlWBt+/JyL2o1RXdYZBVhTJeo5+rgq1MrpJPVc/a0l35DTarl2s7sjMFFu5Lf1Nfp3+BR8x/8kkLaO5TXZUUFnX15ASqDlvJWXkQsqn+vFq03bjoFo5jEa1sla8YyJ97CVWAnU0LdffJ4LfuENT6R1pjZwapwOROiU9Iwfu/avG1rBfIxeuSf6CdTPvsx7wn7/bfLjqdznLDGrvHrX3qbKniylab1UFXbVYx6Gak6hwSOFKZudvoLtGG4yMZo+Fa5jRHusBqJqnXhWqldNkev2G5Uu9dSD6vbYnxsU0Ja/38/U5TgWdLFkKsdwUzXaKyJDf+G4uXDOBX27awoG9neQ3nEV+0xnk1n6AB971ALeedQ2p8g7U4ks1ZOlIKX8H7AR8Dlf45LfAF4G5UsprGjlWIxBCHAI8gpv1+xbwPVzn8TEhxJTIvqcCtwHdwGe8x98EfhrZzwDuAt4DXAH8D26T84ejDmK9xxwJLMXnNuKplQDnFL/KCYUfsaL1oNjX3XNM/oxoE974upigCa/K4ugG0gUlt05Oj4ROwzW0k5T1kpyx1mxg7L1tv+mx+yQpWNXyr3RDyXbgzguO5uoPHsInjpvLDecdxlXnHswe0wIn5KyDZnL6PtP4xlv3DBlcI3Xk4q7hv+xDQ89niS0+r75btrJczqhQhIz2kNOxyplasW1cpJGmQlQEIAkeMbHqPqFz0OhavV4vsNdkmDbxtLMHZelej6mih6OMBVWPebLxfKhn1UwvI6eaZCYtFHoGRSREnxupf2xvis9ejpTyNlpsYgL/cI6qmu1S1NxmCqG6yCIpzip+m/8uXUSRFK84s/z3POYZDRIjUYxGz8hlIo5cSQRKmZlaGbkaRlqoRs40WOq4YyklbC6ybvQN65vLb+Iv5eNC7323+RAA7QxxkvF8KKOjQ6+NU1BZTn2spBKyurp9XU9Gbvep7jzz6eOD/ppJTv+mPr2VSLDohz5/FMGlF51d/MeXWL9nYebDnGi8wAStAfgT9l7B58b0Eo3iqeWVTa8hMHp6aAscOeGEaEfDkfkt4zWd1mvkStKsMKzV+BrQWCAdDPnzaaBaWXle0d9POeZqztAFg/QauWqiOhZlHs981m9/cIr5nN9L05GCHJkQze41Zwa15tlaDP/kGjk9AKGxS/QejQ2UD6hsflw2pJk8z2Q+yarsOXzMU0VtFK0M83z2E9yV+RoXWTdUvD6JXo4wFsW8M+w8fdC617/ne4dLdWbkZKRGzgtKRfpo6hk5f5N3+dQa3ayxBQQOF1i3hfavVp++h1gdCiwda1ZfI0HPyAWOnLLBxkUcDqWQek355JrHBZjYGtyXeoBUv3WSWC8jDXQpqGDTTmKjrwS61HE1BlxnfYS9ZhqErv2gAqSdDJKhyJuNF0NBRbUMqHsySq0EN/OrO3I54Y6xzd3u52SweVMuz7FbZ1DqO4RSz1GUB/dicvNkdp/azivffUvNc244ZC2l3CSlvEJK+Skp5SellD+VUtbHbRk5vgMMAIdLKS+XUv4IOBJoA74S2ffHwDzgFCnlVVLKC4AfAJ8UQuyi7Xe2d4xzpZTfkVL+CjgOd7R8a4THbBiKWomZTlyoe2ljuZzBle+v7cjFZuQijlxJxE8sBY0GA/iUvXVyIms8SqXEIO/VwSip+d6EjFwSPXJGZxOfP3FXPnr0Thy2U0APiDaDjkOtqUI32G3HYXJbluN3n4xpCI6cM5GT9pxCU8r0e6ScdeBMfvW+A/nI0TuFjj1SmynOqL/fOdBvRwCuwalEHJQBHjWkqzleq+SUim1WOT5qrIyiWu0H3Amp/omySIr7vIbwPyq7xvDzzm6hfQZlk1/jNU108ef0D2KP9aey23z8GGMBlINFcbrvyLkR7CQjWHfe9V10qk499Y+fefNcprZn+cE746Oi21PsZLRQ9/juxlq/v2NcwGa+nMud9mHcbx/AnU5Qp5bkiwqCure0KIccuV5PzTJLwW+jkiSeUgvRjNx6JlLwsi8ftf7pGztDZENGPMBJ5ot827qal7PncVX6J3zN+nNdn/m2wnfZ4tGB9WuoG7tGyGgJtteTPbj900fx+JeP51BtjkvKKme16Pchs8fFbh9NwOCX5TP9x+dYD5IWNp+ybuck83l/+w/K7/UfzxEbqIUbn10bu11lSPpkCyUZnH+LJ8JTxqzokWk57ph1a+QUiyBVQTFXxlGOrJ99Gy/6fWdLZZzraj8gwq8FLS/yIWpltcbzy7Lnhp7rgRR3Dnc/ZNf8n/hI8ULeVvxe4rEUarFR6qmR2zIQBAZ6hoKaw0bYAyoj1y5yFa2PTjefZopHIf1q6sYQTbFenGU+5j8+37oz1D+wlWGey36SG9Pf5/epH1W8N9prUNWYPbm8yw9C9CsmUl0ZOcN7TzQjV7luqMsTZOSCNWsqPRX7R9k2Oo434uq+qk8u6j7Snc4+L5jaEekhqmi+85y51IOkVim6kxauZ4539kYClZHb3wgapC/2WCOWCLcEaRRzJlXTaQxjvJeR65PNvnM5TgzycfNO/pj+Mb9MVapG+9RKKqmVKVn2WW4AmwvuGqmcVTVfJLFZ6qGsbr8q/bHFUcC9UgZa/FLKjbhZOr/iXwixJ7An8FsppT6z/Br3u56lbTsb2ADcrh1zK3AzcKYQrrfT4DEbhk6trNZH5YbzDmPP6cmp8Go1cjam3ygVkqPmQRNe95x29OhwumIiBLS/nQy3way6AaNIWjSEgM+euAtfj2TBGokWJiGUkUtY8YQQPPWVE3joi8cxe2KLtp3Yx40g7jtLDM4uXsxD9n6Am53y+x5pkel77EANKWqs6tgQU2ORLsVn5JSCYdRwikOjZT/nlS5kdv4GFrS4DsEzzh6h1wuk/HqQQ2PEKgZllsPyv/SNzJSwmVJc7b+utx6A5Cxt2JHTjZmCtr3297nw5N146itvZs6k+MDEvysjVw9sGfwGR5iLgXjn3cHg06XP8tHSl0LzQNJ3ECJwzjKUgjonaVIQXhZQFDSxk9qqlUmfEz4Xwa8050NhiGwl/Qn47//X3nmHyU2cf/w72nLVV33u/dwb7h1sA7YxvffeS0IvAUKAJBAgDfIjCQRCCOmEkIQUEkJL6L33Zqoxxr3c3bb5/aH2SqvZlbR7t7v2+3keP97TakcjaTSatxNrm5flzctK9xqGk2PSkih2Z9ZusX9HrXB+LHJV0QgGNWf3NR9UYKSCXCEuvKvRlGUFm6q960hK9KocblnXxwpnTbogWMW5UeOI8a4yhP2VsjUri58tyDkz7bqTQNExay6Efh7/vmUFM8/RU5BzXT/6lybskhe9xUbMM54h/TjeFjkv4cUZr2c/fwnE8EBmet7shQDy1sv0EyP3zirbMkMtvEHmqo3Sfje6F9HDXO7Mv4hdl6Nn3lwZ+6WyzaMi91ufd428gBpXbTivEhVmfJi5mLZi91OdWS83CWfyODPeeJPbIuchyLldK2k25xGarQC5J62/Fw+JPoybYz/wLHTvVdsxV/kN+j0NlzCV6b1EhyXI1qITvY0MtO7kZCpozoBqh2slyGdv5VbBgpzhlTTKyFLbIeN4V9oeW4W4VwYZ92bW3jWyARsMS2cTNuFco8TU4shLWOpKApid7CRi1WaOCZLVWUaJAkAfN36UoPl6r1w5CyFuC/Hv56r2CqQK8BTHtwLoL4Tob/w91fj/WbqTlPIzAJ+Q7819n5PZlV2fhm7pG0n289smAEAIsT7XPwCN5kHtrJWxnIvNfG41Voyc4vsviLCVUgwYcyCZg858gblj7Nzm+48Uk4RqWledy8XLx6J3fRVO3mmE4pf5oYuwXAa+lro4hvd2amkcGepCugnk0qaa7oj9xRrLakIXKt9IHosLkidjQufPkevRdWcyBIC61PrsbehAg7Go+sIVcF9MTFe0L9BkackB/UVjjo2Dos4aPO2dv8LErtuwCi1YjSasMWLuBnW9b+1jxkF8oVAUWMd3xEXa2/eY3N/6HPdZiiCX9kslSHZn1kq/uBe8QDDrWK75JWEGbccyjhphK7fqv6lFl7VIUcbI5Vnj0etuPkM/S+9hxe2abJXV2YutPOyuPWlp7CmRCBVk7e1UMfDFRnsR7yiVUmQvH3p96HCiGX7DFnbWEfjEQwG0S+QFxz4fSP2ZGSxWhz6SZVGTcUsrTVkre2UJlcK4oBmStbILsayyLHR8UWufaYmwXCt91JFzuNJrIus9Z9KArfC64fto2Um6q0TStzu7inzziaoYPbWOjOyjCHcIlOzEvh402cN87RWcEb3Hse9OkVewVHMskQJDMzm7S2K8UX086D1wl60AgHGarnwwlU2O+5lyCePEIkfHUZZFzsO10hw3HVZBcOpFoisfP5MteNtwCwSAZZFnMUd7HW7MpGDPEI+dOmRbEE0iSFvWHaqoo8nHzGeBXk+/dVyHtNjn37fBfvboo9OZtBUYVVFvq10Y3AaBT2SbI8NuqyJ8xA9BlNQtxnHWooHEHm7B08Tj6Puxm5w/kmrXyjiSTrdyV9kK893ZpVCC+iHXjHFsyH/dwVvQM2Za/RVCxAHMNv40xXZz5eaVxm8l2c/cV7Vf2DYDEyOCXC4hIJ8gZ7tWeu+3ljzoKtdKc0KLG5OkXUw694Lw7vSOnttVD4/qTEa01eOZS3fBJbuPU+yR38xMF2FBM8sVI3A3lzbV9FdfEnkeF8V+D8BZP24VWvDH9CIrA6GKNCI4P3kKbk0tt0z/relVWfv1J+UJVuYJsAfCr03tcxZWfwB9Iea20gHAjl0/dBXJFXjHqLfXP2m7a1lJO/IsiOg9p8lS5rX3xik7jcC5S0ZjaGtwy4gb1fOpqg0W+jghBt9/MtOzFsfubLXhjiksgbAhmrHiSpKIWgtVvUaY7VLiRf5kJ9l96UQVjk+e79hvM6rxl/R8S/D34u/p2dbnQyMPehZQ/37yQEcsHIUuiPuRZEitdfb1DZu1UsXySf3Quz6OkX3qMaDRfv4dGTQLVHn7Wcx9acxRLR4B/36pJoJYVl0u6ItOt+LBTJyTkdLhDu7ej1p8v5060vpsZlDuQA6LnGuTcH23Eq2e51MvOtHbtYgUyOAHJKPzmYkzABjxoj7d2VXke/xVbr20buZBM2whYk+i0FIl2/GCWuRonNzF0d957j9UZL+DVHgl2aGCRzOyx9808Y712Vz83pFagrXGYtvMdGiuqRwhJWmnIKfHyNlKKZMsJZGWPZ9ZMXIedeTM2MoNsh6rXQpXr3OqNn77JXlv1ueoj0mtdZ0Oi5x9r0zL1SBDGdMlo5a1Kx9TBjfhm/tMwA2HTkHfBlLDmCgXaPmmYrpWuhW2n8je2IoqK5SnkDnJ/cjEkLIENjdDNd1Kuko22bGH2ARJZgxboSQd7ceEmewkaq2bq5F0vB/dCgDbtTLcfAHkEOSklFqIf+Eq8ObnJwDGAbhFCDFeCDERwB2whawa1/9evhCd5HtzX9V+YdsEAEgpm3L9A+y0VjWaMaGRguBe5Jt/3Rm43KwnC5/PRHayDMBOYV5vXAIvEz4A/J/L5ck9YZmoNIe5nvh8glq+ucKxqPdZ+NTEmWq8+BY5L0tCrjIDubgrvRDfTh2FtwytX1s6W4M+0BDkEjKCdZHus8hRDbKp0Qf0yc6d6GVFpi8+9ojxM7Ng1mbsydo9/lTDiS526QI7HtFw8e7jcOYuo4qSWVKlKKfZVouR7DSMIJdGBEcnLnJsMxUHvo6pTHlvLxiiGduFMg3NeiFViQSxyKnqyOV+FjWXdcTk1YzTOr8V1ViLBsztuhEnJc71bMtUADRgM66J3eq5z0/S+zhcuZ1Fu73dheh9Ublth6W+KopHL9oZ9561ozNOhZZEKXAMvymHKL/7dvIIALaLVmNIN6YI0lgSeQ6A/ty6BTnTtcitZJCWIOd87re4lBNUyfVIxo5ltSxyxv7edeTcFjnyGQKfyDbclrITCzyVGWt9HuGKGfyg+kjH36bASV0rw1rkwrpqU+tIVNPw1rd3wxvf3M0oKq0TpGn6vqJubQ0kDuvm1B74IKPP5/Ue9dRUDICtZPzMSKM/iAhyZmzX2xk7gVY/UtuLxhWZ7wdzbrJcK6k1N+V0rc5Iu94hHaNZFrlotjLMHDemoFiDhCWYmqUQNqLWKqFi0peUTDAxxwq1RuWKBaMu4tR1dx16Wd4LplLjhtiPAeiuzNJnFJUQwNFzh2GfKQMd8yCdh8b0JdY/khis0Fffl676lmZx9A3QhdQGV/xfENzvn9/Fv42nqs7AMI/STWYSvxWynzUfNonNDkWDOf7cSpUYiSG3EpAJ22MlhQipkarfZzOUKVdSnHyU3ifIB1LKmwBcDb3o+GsAXgHQDuA6YxdzljGfAK/VcTWc7pkdOfajbQVpMzCmBI9ILOcEnk+wsMsPeO9HM+08F5nouY/7JW4Xk3YOsO+nDsL5yVMAAEck3LlmupdUniwD9BoWYpELuyDPtdja5OG64+USFwQzWUNzZm3Wd6aG8ks0IurhIuIm32JbBb1uNPtml4xjI5zuqye4LCwmptUtlrH1JW7Ntqp39IWzocPWWMZJza6OZHY8S1BUwg5N01yM9X1Yy4tZx89kXY4Cpm5yZYk1U71HM13EImenkK9C0vLz93KlA/Jb5OjRqYHzSzQ63HU3G89QAjE8nxnlXKwZmIsjujAEgKmdN+GArssxufMWpBFRlq2gQr/qXgQpCO6X6lgEsYjmGEN0bHcWOIZfJkKxufg2+XV6VwAk+52rllItOnF65C+YKN5HLiaIFdbnFbJvloVWz0Cb7cZoCnJSSoebbodrfqQCIHWz1IR+0XJnrXT/nb3TN1NH46epvfCf9DQclvg6PjUy5o7V7JhBd8H0/bqudFin/dbuVPHe6nALVvf7qyoaQU084niXBXEDz0DDBkOwMQVlDRnLffCVzDDckDoAbxkKglyF5N0MMaweGSnwZEav5zeIuPOa1pe/pBdY29pIyQG6+E2QWCTAdpl0jB1XwpOMlIiSwvUm2TFyaoWAORdpQlpWOVMI2yxrsizgfUl9QRMzzpMKMb1yLCmriUWOLvxTiFrv3n5Yi1p0Wu6wqqziXlCFFp0HqZJg/sjeZDtVYhYmyn3kUvCaYRlWIhfh/7k4KfJ3rKg+HBdGdc8nd4TkDO1txEQap0fuyfqtaRHdJGutOpbNYjP6kEQ29aITvbDVWmPayU7sMjw087h5L+h2c32dTwnqh6IJckKIWiFE+OCmPEgpL4VeHmBHAJOllDOh918CMNPcmOJ1/+wW0B96chOQfVX7gewbpM3AWFkrteLEyKm4Pa3XoPsw0wefiEGe+6w3Ft1NxkvcmX2LInBXeiGGdf4WjxGtqF8yQQrGFMCCkfndCSnFSPWdy/LjFmoAZMWABMWMfWuV67IEsRqrtlKVLy1v2LtCz5lqNM0XzYTOn+MPqUXYv+sKvOcqUWDtawoL0n5R0VgZk3N2HY36qqijbIUzLlKS7fb09vIn/hcZKlTXkAaFF4OwGvlPXQsHVTZZL5SJiSAsF6KY7LJiejPQSBKUlL2wCulOlqv0B3WtpRbsNWjE7K4fY3znbbg1tdzaXm0oAOiC6F/pmViHBjwnx1jPIV3U0oUKPb4q8U2xocfMKAS5D74Mr5EG9GQmJp2I425jkfyD5IFWEo71inpU18VuxoWxOw0tv3qmmK69bX2+M70oazyYtQvdyZwy8LLIZWetpPNl0iOmJJdrZXaMnPfna1OH4aTk+chAs2q4jiCa+x20d63PX018BS/IUZayMyoyqDMWgmFrd6ZDvh/VoQHe1m4/mAtZU7DqjQ2IGklCzk2ejq2otpJRDQoQV9nXWBR/iUa8l9Hn8sEk8YcZJ7YJNVZtNYdFxHjGEzKWlaTNFOS20LGTdlrkpLST1VCLXErhGk4xxxEdw6brqdnvrajC+3IAfpXa1drHK1mHWUZhC6ot63Ouun1Vwj4PWksRsMsR9BPrHAoVs3SUH+hzQEchtcidvWQU9pjUH9cdONmVV6AwVqMJ3zI8AwDgXsNF3pyv3Rk5VZwQ+ScujenlLE6P3oMDI/91nAx1hfWKtTSF8U2otUKSRolPEBdORVp/scaaq73KD9C5q8EYHylJFaCGIGcmO+mmGDkIIRJCiEPJ372EEPcIIbxW7/sBeMdje9GQUq6TUj4qpTSLbewK4GkppemP9aLx/wz6OyHEAOg16F4km18EMF1kqxFmQ7fwvUv289tmYGyLnLr8AJDfJSLfQ3RfZgaOT5yPI5KXQFP4aa4ngZ0ALSYdbnGmeh0lC1BnT8iRudPk719dgBsPn4pdxvnL1GTicO8Ka5HLcQ83e8S+iQKzJph+5b2xPssaVEVcfPzERoS1JlE/efpyM8fNFtTgotTJeF6Ozvqte9+YJJOshyLhrF1H4aXLl2IGSdG+qdO75hV9+fgZN/lQCVg1ZSLIZaDhouRJ1t9u155c5LTIWdbSTkuLnUTU8ULK71qZ5/gK10rAqTHf7LLkbEENtqIa304dZbkHmhlh640F0RZZhVOT52Qdk45balWlC+nTF7djj0n98d0DJzv7VGRllHMBRdyDyRieNNBfnIuKT2RvvJjRS6Qen7gQlyePxbGJC/GT9N7WPuutLG32orMXtmLPyFMAgHZtpcMtzs1i7UUAwF/T85CBluVxYFr+3PfRxB0j516sUtdKr/g7O2tldtu5YllV35jvRJrs4+fx7wPQ09v/LTMPgHOOajFiodx9LxZLx2e7pgPqZF1Oi1xAQc5YyDYZ53SoUbMR0GOIALvOJ43Jzkcfq6h1Ez4wkoC1i88sF0VTCdmJuGXZooKiuTDejJosQc4U0Bxp/93JTgBikQs2f5tXcDNRWppWnInaBwBsa9JlqeOt8jq1HklMzBi5DlRZ1sDx4kOoVk9VCoscAKwy5vt+Yg3GaHqs+ceZtixLl59zA5xzNi1F0FAdw4+PmIaDZwx2hPwUI6zg5+k9MLnzFozvvM0K2fFrkeuDdbg+diPOjN7t2H5Q5L+Oq0ldV73cWM1nfZOsMdw7gUYP4fqIyP2QxlrWvFZRh2sltcjpfXe+N/V76csil+fa5lvdRV37xAHsCcBfCpxuRAhxCICZAK43t0kpXwPwJoCThRD06TwNQAbAn8i2u6AnKtmHtNkbwEEA/iqlbhoI2GZgaLITTalRK9wiBwg8mJmGT2Qf5WS+wfESlwX7+qtklHTA2DXKr0+YjaPnDsXvTpqj3GfiwEbsOXlAYFO/40VYxILgJus8LCSPhLBoUkxBro9YlyUgVxNByE+ts/CulcQ1xcMi5wdLWJCmxlFmKxKM/kU04bg/XSlvxQAVXu86dR56VUdx6sL20IKSyi2pJh7MseGa/SehJhbB2bt6l6AspJzBnemF+GlqL1yXPATrA7hWqlwIBWC5NkaQsRZYKRmxXNuqBM3KFU6odcSiufoSJYkRcrkiU/c2wLbIeSlQALXrEB1P5qLloBmDHb8tJNnJ3BH6wneXsbaiyXHGigUUTT4QDoF9E9/CsM7fYiVasQm1eDgzxWGFMAUXmliAxiYBsBI1uYkgjcma7nr5aEZ333db1B43trvviSYNS6+0F1dbUZ3lnkgXO16JdUx3Oq/5u6XO2RfhY77f6IrPoSUHGkhSCvqONGOUsopLF8gNh07BruP64qr9fLwzFFNI0JqXa4lrGeAcC+a1ed+Iix4mPvdVSB6wSxutks14TQ4DoLurmZZPSwkp41a2VWqRMxfG62W9ZbE3hSIzq6Nj7KWzBTlzzkoFdEzTPC1yHWjCJkzSVgCA5S5KWR55Jmub6V7XIeOW4H9u7C7cGvue57GrFTFygNMiN0bogtxb0tv7SoUfhRLFWX6gCJIc9HFF5/m1LquwNxJPV5+BfSOPZwldGjKOtQ21eHollqEWudcyQ5EmmZNpQpZjov/B2M4XjaPrxFWulaCCXNyxL/2NinxXtiJi5IQQOwsh7hdCXCiEOEEIcSuA3wD4jZTS/Va5AMA0AP8WQpwkhLgBwCXQ68C9Tfa7C8CTAO4QQnxDCHE6gIehX5MrQrYZGDM40l1+wL2Yy5u1MsCdVGnf11uaj82IIo2IEXcQ1l1KtdTJF+eWi+a6OL65z0TMbffOMFYIxchamUvj+ZYcjG8mdcuBGdtjFrwMizmxtIjNSHQ6JyU7xjHuKzaiGK6VNMYgyLixLXJ6n2NIW3EvXu3Qqzyuv21t22eK7XJJXz418QheuWIZvrZ8bFFclyjVPksbmOw7dSBeuWIpDpjm/ZIN69YL6PWQrk0dhp+k98m/M0FdR044FqnmSy6FiOUOGyeuleELgpPPrr7QciercpSiMPtpWnRMDS7Nvkehgj4dw698arvh+hkpUwbrfepVHcXs4fmtoLcfPxP/OntHHDbLTj5Cz5kek1qRjp2nu0b2ayjMHTsXphW3SWzBXfErMFZ8ZFlPTPaJPO7528HiC8ub4xkjVbfK2uEW8ExBTkppuaCtl/U5lYgdHmHrZrtecnbvemdbfp4y0xpgaumPidxnfXdDan/rM60PZya1UI27IJy+qB0X7jYGj1y4GPtMGYhbj5mBtl75BXplzcuAc4tpkTMX0YdHHwRgZrjW2zIzDsdF2nfmSjMV/3OZUfhQ9rXeh6OEXkPMdDnsQJWnRc60GG9AnWWFNePNzDheR9ZKD4scfT8GwXxU9fg8ozSL2IpdjOLeCRnB8xlbSbdfxC5T4a49WEOU5cM0+9rtGnkB+2iPZvfZYZFzu1bqz25fsdaK6XxLOhVQ+aDCGH2GVKOm0ARMfjBj/9qwXrnPt6O3Kb9LyJhjTqUu97O1N63sladH/oKnq063xtEW1GAj6vE2uYamG7DJiK43AJAYOZK1ks5x5ryYQNRaz5jvqWLEyIV3yuxZPoZu/boAeo23dwCcC+BG945Syr8LIfYHcDmA/wOwGsC3AXzLtV9aCLE7gO8COBN69smnARwtpXw3TJthcBQEz9IQ2sMv3zo8yOJPNZnbbjVbHJqfsBY5lYUnmavAWwlxxkwU3yIHCNyW1mN5HstMRBWSWCG9Qi/9Q2vKpTc6X6LVDtfK7ptw6TlTi1yQicl8mVYZgpwqO5cJHe/De9fhF8fORE08ggfesK9BPECqbUeNMAUqIb06HkyQ04RANKLldGfsaXKNW4cgJ2xBztQgViNhacFV5Qfy4Szqrt4vVwIXcwyZ495c7K1TBPvTrJWq8/djefvZUdPx6yc/xP7TBqEmHsFPH34P+0/zjgUF9AQBY/s1YOV629VKdcpbE/bCb8KABvz3gkVora/CxMv/nbdfYaAFeGdob+PO+JVY65H9tA/WWYmWTJpIDMvnedx63Vn0bIucdGjEc8WZJRFBSmpWzBYAUpYi+7611bstcuSz4himVc2Mz/lG7FfWdzTDJS27Mlp84vgtRRPq8gFe1FdHcfqikcrv41ENiZTp3uXdMD23oNZ+yyLnSp1v1kQFgE9lK7bIKtSJLowWnyjjoE2iSFnFv1+RI6DXL+yHSWKFYZGTlnt0J+KWJ0ur2IRadCIDgTrDM2C9rMsqA2BaBTtpxlMvQc7y+HCOsdWy0ZFYxY09bwtsRg1asBn16MC8yGsAgCcyExwuwB/KPphkxKwNFavwPnnGaizXyuxxfnj0Qfw1scCxzVRybJI1yLieIfOZGyxWW7F6r7iy/uaDjo7mWrtPNDslpRuXFRZmRs9c9+TI6APK7+ZHXsPHa9VWuPOjd+L36cW4MHanY/tWoT+/9Dl+Ww7EXNj1AKszelum9TJKygzQ96ZZE7cDVbYni5HttErkt8jloyIsclLKd6SUS6WUbVLKainlJCnlj6SUnhKBlPIvUsqpxr6DpZSXSymzbP5GzN2JUsreUso6KeViKeXzhbTp/6T0/6hrJX2xBHWtDPI8qSZz062mWWxy+A4Xkllxx1G6WwQtzlzs+JJiUYwYOb8vyjfkULwo1S9ov9BC3+mNnzu+swW5mGPRqiTkbaFCIn0hBXEtsixyRp+9NI805bvmWoQtHtsHc0a0OoQjP3GB1+w/CUNaanHH8bPy7qsSvIJa5MxhVmhdsGKitsg5E9iYRVlTJGvlOJLRL2zANh16+ZQhKuy0znoBZ2rZ8YKO2wFN9sKLWnhVR6MLmz4N1Th36RgM612Hvg3VuGLvCZg8qCnHOeg4xpMiacBTH9iubLGohqGtdY508sVmo0vobRAdlqXgo4wdUWHGAlHM690lY4GVf5GMkc47YyeM2IKqrMWqE5FlldtszDleMk2DazHqKGCsuNHm2G/wiJHZQK5VF+KWtdjU6HtZ5HzNw4Sl471LBZlUkfbqyLhQKSCC1JEDnK6287VXrO3fSR1mfZbQrJiwAT7i5PqJtZa3j/k7s2zNCG0lYsQbqEPGLddNANhBew9vVh9n/b0BttW2xhg3cWsxHUFaM8YhSXZiJlszXezciXeOTVyIFzPt+E7D1/Oeixnr2Ut0YImml914PDPBsc/VKTuBh2lxBPRaemZipk5U4ezE6Y7fuUteALZA8KWHcuVzQ7HSKjZZ7T5HLINBmT+yFcfNH4avLR+LPgovgKDjOQymkqTNI+snQNbQLt7I2Ja04bCvuzsu7vDog9g98nTW701BjtZndYcrNGScfYpb7roRh7JqlvaW1ZYj2zPpe1jPN6BCBLltEXOajVqulXGXIOF2rczdXhCLnMpP3jQF16ALrcQf2WvS8MvPjpqB3500x1HkO1lAjFx34nDv6haLXPHZiiqrkHt6q9MFilrkqDXp2gMmYQfDHczkot3GIiw0Ro5aZFYRITMfllucYZGrJTWJzEx1tC6gKuPcflNtbbCfe3HorCH434WLfS28VQRdWJtjS9W9Ipco80VOQY5kW20V2YIcRaVV/OkR0wAA04Y0Odo2ocqdsM+eOU9ViRR6oQPNxhy2TlE8nD4T6YzEDYdOwdFzh+KO42dBCN1KO7jFWxlxw6FTMaCxGpeSeS0oER+Ko15kbBU7qU5QPkeLdY1riMXcZIqRzVFPTpN9Ql4xwiYRadZlkqi1su3mVyBSgXGzrLYEP69HyG1R92ORs2uFdTnqWN2V3ilr34+lM7mWlyIriJcAAIzskztrajQicOD0QdhhUCMOJ666NDO0Q0Ec1CJnJTvZjBMj/7S2P+8SEMz0+b1zWE1Mxglb8bPSSJRiJjwZKj63rFSAYZFDAz42lAjnRf/oaGu9rCMK6M3G//pzv1b2QkYYz0/aVgyaQm6bUS5htat+2WtyOPZNfAtPV8/z7D+dn8xQgmtjt1jCvhnzZ/IEEexoGSiauKRDxvGXzAKM67wNxyYu1PsnNlpudyamIm2NR4HvNa7z+DjThtXw/w4GgM1dtmAhhMDle03AqQvblfv38eHmWyhm0pNmbPaMwTwucq/n745IXGp9fqDqAhyg/Q+Ad1bQU6N/y9q2RejvvQ3k/bdR1uDkxDnW370yxnj3KD8AZJec2ooqSzHtFuS62yK3uxDiXCHEudATfEgAB5nbyHe7h+7FdoyVtVKLOV4m7uk2r0UuwPwcUfhpmsGZcZFGm+Hnn5QRz7T5fpDQY5Pmtrc6FiHp7ijCVARUgvRD5y8CoAeb56OnBTlaMDO9db3jGzMGoEvGHf0a0lKH35442/p7/shWnLaovSgxck9nxuLpzBj8Kz3ToUnNh+U3biwQ60iGL7N2VIK45DoSFZCnZWy/Btx3zk549ut22mc3V/tJFpCHIcYCvzqmKd0yVYs2s7eqRdWWrmCG/mKMuVxNdCFmKQvMQHI9Ri77vL3ilgBg+aT+eOGyJbhyb7uGZV3cfnFRId09112ZPAoA8LvU4pznQOepenRgofaysd1bGKPWibSU2GfKQHxzn4lo61WFF7+xFI9/bWelBWP8gAY8fvEuOGmn8BV3/Ny3Hx02FQDQWhfvsbmFFsKmDBars1Jnm1QhgbONbHGmIGZybfJQrJaNWQXcv5qw06JHMnp7UtrZ/ba4xtIGd7FmwFFjMKsGmAs9SZL9t+N9q3iBdlrKzYSjBMEfUwuz9v3IJch5Ca5Bk43kIyOB7x20A/76lQUOiyMNX6DzY9DDm66VrWIjRhoWoh+l9s2yTJhxTCPESlQhgeniLQhkjOLK9rN9c+wHuCX+AwB6vKvpfm8qWxqw1ZHd0fQGMgW9GaS8xf3pqViNJqyBrlwwhUjqmpvRjGtCLHKmZ4dp4flCoXBUxoWRL7wSKT2ZyVbuvGvEVtURBaVZsgCwFQYdqHa4N7tLOtgWuWxB7k1XPFyY+HtV4jAVpy5qx7z2VlywbEzgY/nFFLQ1Ia2MsBTTTRcA3sjoyoyMFFgLpwHi+/GbANilL17ODM953E5Nn0+oInATanFfZia+lzwIANCYXg8g2zBjZtT9ZuooR5sd1CInUq7kNeGz3PoRAQ83/lFOUexbnqaWMkaVtdL9Yik8a6WNajKnbnFmMV09JiXcy8dZ2NZuo5BkJ92JamE9rLUWK67ZAwBw1u9fzN1GN7jLfWufCbjsr69hcEsNPl6bnWVpg6xDb7ERyS1rAaKBo1krab+klI4FzaCmWmt7GOgCswtxHJy4PHAbpoaxN9ajCgnPCY4uTnK5wY7umztb42GzBqO9rQ4jCqgR1qdXFe48ZS5qqyLYTMof0JiVaEQgkc7+rdl11VhJBVR0RIRAusCp152u3BwK+naBLah2xEAlEfGMgaSZutw018Xx6Xp7/FbHIpYGmLqCuWWnX6R3w5OZ8XkVAzSlfS+x1ZpbM4r5iwpp7tqWqpiQYkKfG9WjN3tECx65cLGvBBfF4vvJg3Br/HuOrIwAcHbiDHwndgsgsusvfT92k/X5P+npju9+mt4bP03vBfd75G+ZeahKJvG92M1W/UhqkTMX8V9PHoezonfjK4kzs/pK3f7p/feay4QQiGmapRDyM1WbgmKVSEIj2VNfltmLQLdFzssjIahrYz7ouKX1LOmC3FF+IODxTSGnl+hAL2M8PJyekrWfmeJ+WeRZXCj/gBOitpXkJ6m9cV3qUFQhgWWRZ63ttJ6XKcjUiU6HsGPe06czY7FTxHbt/Gt6Hs4y6qOZFrlGbIFAxurnZtRAasYSN2PP0ebQMLOLui1y+aDXc6NLufB6ZqhnLTpTyfCt2O14LjMab8ohjpgvKph9LlvQIeOoEQks1l7E+2lbsMvlWul+vtyCnR+Chr00VMfw2xwZxAHguwdOxoV/ehmLx/TBg29+kXNfL+j96SPW4QvZjOFiJfbSnsAv00sxQtMFuZ+m9sLtqWU4L/pH3JHWSz4cnzgft8W/52hnsCEcfyj7Yn263jGuHGhRAEmHctIsaWEqD0zXSiklNGSsWHFTyfl4egLoa7ILMYcClMbrFWKRy/fL3CpQpmCcrpXq/fILcgGOqbDIUTeV8UZwrpn6Nww0fS19gb2zKrswZjnwxsqN1udIDqE6F0Hr9PjhoBmDsWhMH7z1+SaceMezWd/rwvZKpLesBWC7QdA6cvR80lI6BbsChYBinPOrmWF6WyKDSeJ9a0IE7Pg5h2sl+W1Q2VkIgdkjCst6mpYS/Rr1SX1rl4e0hhxFtvO4VgZWdBRhyDnjc4UjHhHQF0VUkItGYlibzhaY1yC3GzY9Dk35n9v9S1iFpHNBtePHR+5FvbEgfCA9zXP/qKKQfE+hXFO77oXKvbO7eFqOw+SuW9EbG3FH/Bo8kxmNb6eOQhJRUgTeKcgt1ezU6pcmj/do1XuQJoxFjWmRy0hpWWTM2JRfp5fg18bCzA21ttL7r7qbMYdyxam88IIu4ppJuIFXDODH0lmV6R2PpB+xIr8fqAKkOuZdQoMeUZVGXsUXHlli3/FIaf9EZjzOgm6RpUIcoBdl/lVqCZ6o/qpj+wsZO0bcTJLVC1sdWQVNb4yfpffE+THbrXI9iT+kdcaocLhJ1iAjsi1y5jUzhaLVJGEYRfXep+9Ot0XurOQZnr+hLnb/rLpE75KR1j4jhcN9L4WoFWd5WezX+HnadnazBDkP10o3b2WCC3LdoWQ/aMZgLJ/UHy9+tD6UILcRdZZg20+sw6sSeKjqPADAUdH/WHPRCtkPq9CCC1O2nenBzDS8l+mPdm2lVbjerHf4mWzFvzKzlIKcuWb6kNThW2F8NhNANUr9fkgJzwSBn6I3Nspay+2W1pEDnFbZRI4YuapoBNkOoTY5n2op5X+D/svVHpNNTNoWOceLxbVfvsVqIGFDYZKjKZTHGwkM3skEq0NCcVrk7KH21qpc9UBKx3urbQGzNmAmQpPuSsc7uKUWEcV9M19qcqsz0NzUbG6R1U5BTjFZh3atLIKWeQ0a8XZGX/jM0153FQPX++6wyDkKkfa0O6tTE06FHrpQi+dJgqIaK0ENo8U+exq7ZX7c4opXSmtRvCBH4YOM/mLbJGtwfWr/vO4hdBFUpVhUhk0CQy2Eh0Yftj6rUnBThVYhdeHCElNlzSRdUblTulPpF0r2cQS+RCN2T3wHl6eOs2JfzUVItcO1UiJuKF4uSx6blc0yF11Gu2aMnJRAHZwWuVzQLLnupBVexBTKA9WIo14qZgr+DhnPyroJ2KUbTNyJYwB/c+U1+09CVBO47oDJefdNS4VFLplfueRHAbfKdS9Xy0ZPF9bXM7kVLee6YtsAu0wAQCxy6ESdYaVISzuZTQIx3J5aau1P+2AKQY3YYmUXBXQhK2NZ5Ozrob//pJXOfrWipInq6tD3DV18/yK1zFPIBbzdu82ELhtQ5zmevOgNtWslAEzttC3jD2S8FVi56K6wl/qqqCsHQZBfC1Ijb60jbrBNbLCEJPfzZ/KLtJ5d1hSazIQ8K2VrlqLiptReAIA/pBZZ76o/pxfg0fQE/Cm9I16Vuiu9OddUy05A6qpw70zvwhIggezY8nuqLrM+u0uyUPJlHa+U8gPbLA7XSoeZwblfvviIIA+Gqi1aT2WCYZFzaxmDoMpE1511kAph0sBGPLNC958OG8vQHXJcviyHZvY00bHesd18qW1EraNfGZdFziTsWrZYVsiXZTtG41OM0D7DW2n9hUgFg0TK27WyFNAFFD3/5ro4tiT0hUi+ybdY51AMEUR4CG+ULa5FdQYRJBHFXomrEEMK6/JY4kwcLrHkulE310Kuy5/T8x11mzbKWkd2QUqsxBY5ah2hZ5xRjC3Kf85ZiD+/8Cl2n9Qfc76jTr3tRpX+XhOA99LfiVV0XdiLlhXVdla+1wzLul+SLkEuk8lYbpteyXTcUOFtC1ksq+YyRwFjsj1fjBxgp+D3ShUPAC8SC9Nf0/O9j+/jvXLorCHYb9pAVPnIhkvX3WrXSvuYR84ZioffWo32tjq8sXITUpncd91dB/Dh9A6e+21ErWU18WJu5PWsbT9J7219Nl0ooyJjCSt6Cn+771RIogK8aZGrFkkMJbXYVslmSGH0P0OTnejJa8y077mS8HhBH8kqcr63ptRpIlTCImD3n3JR8iRcG7vFERcqkEF/oyC7KYC4n+d1aMCwzt/mOQM13ToPUhdf4uLshy/QjOFYhYniA+wUe9lzH3eyF5ONjlqQ0rLIrZStWYqKa1KH4oepA9CFGPoZNzqBGI5MXurYz3Sx1CCBZIfSIgfoVrxx0A0juiDnPX/ki/HNBWetLDFRU7vgylrpJn+yE/+LH5UgR19Qpmube6AXwikLRyAWEbj/vOxA8XLg8Nl6oGxdPOJMTR2A7hAw7CyHKouc/iLSutY7trcYGQbXyV6O36YzzsW6uegJ62JZrCQMZmB9I6ljSK0sKrePUsh0Uwfbz0XfhmocPnsIlozvi2UT7HTh+RZt5VR+gOI1zja7sm+Z2eA2o9YhxJ2wYHjO8eBu+roDJ+PYecNw2EzbalaIVfuh9FTH37lKYFDryIaOpHK/7sJZO4+6Ptv7qOb15ro4jl8w3HLv9YvKrd4v5jios1K9O6/bu3lqiLkxn++osdAW0hYszAQ7uXAmIsiflCtOnkk/70yaTMW0yKkshVtQgwmdP8ceXVfhIuntYhfzef39CHGAU+inFm5V0orm2jieumQX/PFU74yM+XheqtLZiywhjl47M+b+8fR4zOz8MXbtug6PZeykU9RFsZ+RaG2z6zq/RbyD0mTpSt2599KeAKArcDpQbWetJAJrJiMdrsGqUhmq4UE3/yG9GJ0yhnvTM/Ep1ErvP6cXKL+r9hB+zcQ5vdBhFREfKz62rrH5nBV7vVEsQe7MnXWlxrUH2PfYqcQL1p4pCB8afRhLI8957qOKCTTfAXoinS6rBuEq2eyod/nn9HwAwhC0RM73mMN6ltQtfTS2cyvxYKGKgqQiSdiD6Sl5Sq3khi1yJYbGyOVy9SimpUel5fWa0IIGAjtwzQkXLx+Hi5eHT9fd3eyzw0D0bajGqD69MPOq+0O1oZpXI5oIPUmaTaomP9O1MkYEOQ0ZK6ZpLZyCXLla5MzzaBJbLK08HZOqZCdhhe4w3H7cTDz45hc435Wly8yEec29b1rb8i3aivUOLkYz+drIKsSteb86DpoxCOcvHYPL/voq7nruExw/f7jzZ64DHTwj++VbiIDrznTodgml0KO8sbLn3b0dWU2pxbwbteKqBDx+MRcwpiA3nWQRvCx5bOAMx2bdQQ1pIJN2CHJua5AX96Tn4bioXhz9QTnT2q5ylaXCew4HGAsqYPQ1BAzqueJmC2rwmhyOOi0CLxtnLFrkhTd1645QQc4+tuaytlcHLGNxcuIc/Cz+QwDAY5mJyv1WZPpaNQcBYFzXLxzWWgD4fuogrEYzVrsSwVBFkXmdt7iUR2+ThTp1V/uMfD48+iAA280uY1nk7GQnGSldybS8Lb+q9wpVND2RmYAdum7Jaz1+WbbjpMS5mKO9gZcy7ZitvYEjjCLWXuPJVGpqQqIRW7AWDZij6VbNz2WzlfhJv7fFmy/WbvG2qAbl3KVjcMy8YWitt+fjXOW18uHOkuvm7MTpyvnCTEhTJZKWchvQrfkJxHBd8mCcG70L308d7Phdrte3Q5BLbIGEdMS7OT0F7M8pGfUcK+ckT8/aFgQW5EqG/vBZrpVa1DXhOgd6MeOAVJqGNCJIyIgV7wA4NQtBKUXcSSFomsC89vDJXQC1MFSQIJfHImcusquSG6xtjdgMzfDBXysb0EomJSllURUDxYoLNF3gGrHZetF2OQS5/HXkuptFY/pg0Zg+yu+pu16+DHU9X6pCjXR8zh6n7no4GYUgJyBQE4/g6v0m4bBZgz3q8+U/50JCLt3WklxxVnTczB9ZWPKbMNC5gl6V0X174R+vrMzavxjQMbd0fF/c9/qqHHtnYwrGtaITbViP38WvAqAnK/pVeqnnb2gWVDcpuvhKJ6ERQS7lQ5B7QY7ChcmTEEEGj0WnA4riwCbRiFOo8fpM6UIcG2WNXhhd6NfK7WbsherZLtQi6kZ1XUf2sRUvKgWxXw+M+zIzMa7zNmSg5YyBPTBxBZ6tPg0A8GZmMLye9Y9I4giKU2Bem7UN0JNenJI4B5O19/CfjJ0Z1St77nrjXWIJcqSOXFpKR9bVLpVgrrLIuQaL37Tx/8nMwH8yM4zfRHEEdEHuL5lsN1xqaW4RG7FWNmC8+BAA8GxmtNW5iF+faJ88/9H6orVFhTggO6FWEIaI3ElS/paZq/yOJpIZADuPgKk8+El6X/wkvW/W73I9q47szMmtkBJWrF6XjDrGBJ0vvOqvPtK0LzZ8Hj6DNsCCXEmJIG1b5KLVORekxbXIqQdoJ6oQJ5oFVV0oP5RrmQE/jOpTj3e+KF52zagm8uiU1Ji3XrU4MLV31Ym11rYWkmFtreyFHZpqAWMSmzyoyVMxEPZuFWtompqzBrGVCHLems5c5QdKCVVe5NO+lzrOj5Kv9ERWvSThvcg2Tyke1TB9aHbwuSOnh+KYhSit3OUPtuQoh6AJgav3m4S/vvgpvr1v4bUFg0Jj5Gi5g1MWjsDaLV2YU2BmVS+o9TxMKnwzjqMJW/DT+PXW9n+lZyp+oVtYU4p77Ui5nUm6LHL++ndnerHepyr73JQKNWUsqHrMbUItGtCBQcZicr2PmCqH5Y8IsvniZgvlJ0dMwwsfrcPRc+3kI6pYwCCW7w4fwuuXaMyKz7ogeTK+G/uZ9bcqQyRd7FqulR5K5H9nZuLfmeyx9qvUrjgqanvRNEF/d9uulbaAn0q7XSuDlRopxh38d2YW9ui6GrXoxDMyu24jteiY1u9aw3WPjr9oRAA97xUeivDJToBrUofhF/HvWn//NrUznsuMxkDxJf6U3jGn9Z7GU5pjC8ifTClXHx3KnMQWADU4LvIvALBiL02otTnpIcilIoXnjGBBrkRIAPO1Vx3b3C4QlGJq73PF7nQijgaHIFfc7GiVwpLxfYsqyBXiLmbXHfP+3ix8WZfZhChSSCHqKJy5Dr3QUBPFv8/eCcl0BgOanItymfUhXP8KxXRXqEWX9aJVaTvptehJ18p83PnsJ9bnfPe8kEdalbQiLHTh67UIdrsoCk0hyOU5jh8hrZC5zp35K6dFDnpcrBkb29P0a6zGUXOG4svNXdhlnG2pqI5FcOU+ahe2QogQJV6YhE4rpS5cDhBfYrT2qbX97vSOyt9oOQaro+ZWOgkh7UWQX0HOhAqpKm+QMC7ZHbIKEECbGXOsSJ5DoWOYCrJUiVrsZxgAdp/UH7tPctZb7CRulvSMe8Ij4I/pRQ5BTkUGGrbIKtSJLrQbhce9im2rj7PQIch9I3mc3q6Ha+Xrn230VYhZdXWKpYB7TQ5Tfkf7ZNaDrfXI5lrsuoTdC3kmAo49d1bUS1In+v6tl7UXyG9Zz9XHTsSRkUL3ekpsgZTVWBjxTsJCj2Nm4e6SUUvgS2osyFU0L2dG2H80DQaJlcyiJ1wrASNAmXytCgTe1jl1UTte+mQ95o8szNXSRFU6wA/5XCtpcdAWbMIXaLYschtljZUZbky/3IWyQ/evSIKU+YKqFXZAstoirFZ6lJJ+DdVYvUnvu7sWm5tCnmma9avYdm+v9ra4FlUyonCtzHNKft7fhSg93IKcHze4UvKtfbtHYFNBLUJhFvJmkes2sQFPZ8ZglvYWXsqMwGforXQfz3U/kwW6VjqO40eQc2qA7I85LoV7TFG3NxVUqIxowvJOocJzIULc4jFteOit1bhot2xrjpvJA5sAI2ueIyNqDwkBxyQuwjeid+Ca1GE599uCGtShC01Cj+2mdeby8bJsxyFdlyFh1Ol63RCSvCxyEs46iMoYOcWY6AkPkAw0K8ylSiQACSvRCX0nxot8D5tqg1kng+B49ALO8X7q5qnYiipL6DLjLztkPG9ykUhON2iBTsR14TrVmfMdTC1ya4y1WhdiqDLcwFNFEOQqSZzf5liPXvhK/Q+BEx8Emoa4tIVOivnA5kpO4X5pdeZwTdqWaaiO4TcnzsHpi/y/THJRjIQgKkGO1kJpE+sBODNW+iVs1krVqQV1I6JucYPEagDeqZlzHbPUnLWLndWt2C9ZiqMGWxEkuXz33p1BDkKlA8x9Y6jQrzpiITGXG13jJZfLTeU6fofHESMWQgFjJr9qFputekx/S+vxKSrBMJfA6HCtTCdCuVaaUGuXSoeikONyXgm3MslPuAE9Zzr3F2tOuOmo6fjbVxbg1IUj8u5LF+dbSaabYiWpysd/Mztgl8T3rfgwFe443P9lvEsdqHhKjsMLcpQlxAHeFrk0KXGRlBFfSXUoPeUSb1rlTKGzxrDI0WygxUqeM32orqC5cFl+xUBYVKU//JBGBK8apU3uzeHG7Y2wrHInGsXqs95nHuR7VC0FQKoT0lFX1nl2tF7ix0Y2UmpxTUfs+WTmMP0+zBruXRNPBVvkSsz7sVHAID1wN5fGIq4onhsG4TJxUy2q251he3WtLDbFmPxVC6KNqLO0d73FRkDaNY9Mt0s/GrCwuWlUbUc04UhQkg861vaMPAkA+ATewfG5EgOVkp3H9sGu4/qiOqahoSZW1OBxSlUsgk1duRM7BMFx7z1dK11uTirXyjy3ws+tKmR96c6aOFZ8pNw3X1zgtggVJMKc/6tyOLbKKtSKLiulvJneO6aIA851P5PSKchp0l70FGKRUwty3vNGToucS5mZ9LFsokKS5rLOFYOqaASTBvmzUtAajc119hzbU4KcX6j1fLOsxtuK4tpB8Ep2kkzLvDHYQA5FRw9dtk7E0AsdVl9t10p7PK7dXJwsk78+YTbe/WIzJg70Vw80DIXm+Tkq8TXsFXkCf87hxq1iE2ocIUN+kvhRT4IosaqbWGMn2aln3TU4IXmBY7/PpB3rbJaVWCWb0SY2AHDGyO29wwB8Z//JGNISrKYcW+RKjHNwe1vkZg5rLqo/O9W+uydzGhgKbL+ulWGREjh3yWj0rq/CbrSmWAhttRv1YkNYbomm1s60aBVUPqJAgmZoc1uDATjqvFBo0+W0HtE0gVuPmYEbD5/WrQulqiIqdoD8WSvdLorvrO7wbCffGfuxthU61/0zPcv6/GUJx385Eif1yRz33KdMtxXVeCrj1NqbVnPVvc11P5M5YuQyMnyMnMrCrLbI+fdSuSO1JG9fVBY5mtSmpxjZpx7fPXAyfnjIDhhI4qMLcffvDqgLWr3oLKiulolXHblkOkNisHMIckrXyh62yBnWwxqPcIPpw4JZblTUxHXFQHcqRekzEeYw69CAO9LLQhXO/sJV7sKrdp+bfAoYq2xEqhOatBUF7mRIT8uxuDp5GM5OnG5l5qbCndu1cmSf+sCGGxbkSoXxnlFl36MD/cg5zkDPQiHluLIWm9Qi1yVjgd0OGODMXUbhmUt3cWi3VIucIIt9PwUqa40MV1O19wAAr2SG+24/dNZKRbeCJlPo8NCS3YMdMcNw+ziE1ByLFOCm0VN0ZzIBKsiFdYmlKDNIGv+7M8htUiQiyLcQ8HNFNOG9CPbL6cmz8XFGL877rdSRyv22P3ucc9yELQ/zhnS+j0wraDjXSrKQTncVMUbOex+/VjgKzdj4QaYv1viI16FKLNqvWcNbMGt4CxaOVheP7g4OmjEY+011Wrg+XuutjCkVIzS75MYGGXyx7oW1fsnKWqkv5HMpqksZIwfAKhxtCp1m9kqaeKouXvj6rHd9zyjrnXN5z761380McPzdaNTYzYXbIufGdq3sgsjQecstVgn8LL0X/pKxi8JTBWNHrBmFwq6VJYYOD5Wmp9gaoFTGluQSVKqDswr9hoDFXd3sOKo4iUIqCXNRLYRwZohTzP6xiIauVMbzOze5xoGZWa1WdKEKCYwWHwMAXpT5Y/x6VRc2Dai02UEtchtdmrbXMkOxRdbg1mNm4PH31mAxqd8Wc2j3ylOUi7iUNIVmqHOmMe9Gixz5Y2y/BqxYszUr2clmt6ul2cc8x3GMYR/ub7kyHuZix8T1qEIyZ42n7dCz0qHpDXv+/0rPxOnRe6y/zUVJmPdXIssil7EGUdAYOV/JThwWOX9CHY1JWg9/Mce0L/RZjUU03HmKHlPYfsk/Q9cW3RahqeFvTO1blDZtixxxrcxkUG1YuUxhKQg99box5y7TtbIOuuBN5+JClIW3Hj0DP3rwHXyzmzLkusmVld17/+JldX1POgW5R3MUtreOT63qEQ3ugn2WEiDV4fAkSPkQq6hFcG3NUACFKVXYIldi1BpCuggstiBnPx3uB8VM/QsAfYzEGY5e+ejKW9/eDX84eQ5+fkzQoNTKh76Y/WSIC2K1yjUOTItcDbrQGxsQMYqBf6gowAoA+08diN71VTh1YTuA8DFDqndJUGtKAjHHi3UTaiEh0VQbx+6T+qOGaB9pxrVyLTxPXZeKEeOqqoFVFKFOOj+es+tojGirw1d21hUB7uDw3ad5J1koRoycI+Nf6LlP5C3UW56jpntxWnLD8bJsd1ho3zUWSarH3b9rZQKaY0HUvTFyKjdLN9S1skNVPNoFndfrquxzdBahtxWdxbCsVDpUiXxbenlR2kya7rkKi1yYGLmecq3cYoy72dobiCOJuNAFCZoUphBBbtfxfXHPVxZgyuCmgvrpF4drpY/9gyqCc+Eu9fD15PE+ju/fIqeR8ZX0MW89kRlvfd4Y65NjT3+wIFdinEUSvRdqxTblp4gVbuJAp5vI05lxOX/rZ2FVFY1g9ojWoiZoqRSokOyoJVQE18pcu1qp+9GFBmEH9aqyPgLADw6Zgqcv2QV9G/TfhtV+qYZEmJeMe9GkLOxL2i5XrXaMvIiCZqsza5stIIs9VaKG7qgldNauo/DgeYswpFW3krotcM2N3kHx+TIh+lkD0Uxs3RlnuL0nOylEAXJ44lK8lhmK8xKnQlrLiOAL3ww0pMzFdsrpWllIHTnVvXX0xRHKkMPbgcxJXnG8XtBrSwU5yvcOnIxj5g7FX8+YjztOmI3BLTW47sDJvtovBjSGO6yrZzFlmkMSl+Gx9AQcnrikaCEdr68y3oXE9e3DNVvz1ikF1OcW1AMk7DUyk3MsjTyHIWKVtX30EL1OYHVMK6hUS0+jWg+oTiFo1utcPJ8Z5fj7c7Qq9rTJt36zYuSSWx0KKD/z1t3pHXF9an+ckDgPWhEE1u1vpV1m+DE3F9t1LOXKJLjimj3w5rd2AwD8LL2Htf0T2dvoo71vIanBtweoUOGsJeT9qAURdnLX/zMscqILjcL2/84XGFyM+6kan6qJOKcbE3mxdqBKaTWg1yJIZsyehPYxqFLjqn0n4tmv74plE+3FFh1CdKFajBee07XS/sucn9yulYh5j6t8UxVdeKgECSqYdmdChvIcNd1LVaywrJUmL8t27JH4Dv6U2SnvvvnmOMsql04WVH7AT4ycQ3jzGadDs1Z2+hTkEsRdnlrb6FzZp6EaV+4zETsMbsL0oc145MKdcTCJA+5uYmRO+umR03Dl3hPw0PmLArVRTEHibTkYRyQvxeM+3N78kpTZWStve+wDy7Utl0VORdBXZtgr9GPiXrpUe9b6PGP0YPz2pNn47wWLK2o9ppoHVIqeYtY53IIa/D09BwBwQNflvn5Dn1UvhaKpPL/vxffxj5c+trarXCtpG2lEcH3qQDyQmV6Ue8iCXIkw3zPKdMhk36Jb5MhbznyZm4fuRBUOS1yKe9MzcXTia1n9qiQNUCmgQrKfGLkg19OPa2UtutBgBPJulDVW5q/uvGuqtsNYIWktuQ7Elattet0efHOV904lxiHIBXwpCSHQu77K8eyrhKBiWOToop5ecvP4CdeCR8TCFTGtitmLWlVsKD2fckuRXuk4yw8Uu3XvBv0LcglHGu+gVhnqiqVSEtCe+E92Ety1kgpytXF7YVdOw3m/qXbcUG08imPmDcPw3sHi4stdkPBKdgLYCURCxcj1UKKOezJzLWv1jtqrAICMFEjGmzCvvTf6NlRX1PyoCg1QrYGKfW5nJc/A+M7b8Jwc42t/x7vXQ6ForrnWr1+PGJm3LOWBuz0/5xNyfc3JTkqNwoXS4QGiuLnz2lvx+HtrMCLg5EuTnZjvOzo5PZGZgCcyE7y6WFETRymgFrnVm7qsz8rU3EFi5HIJQKYgRyxy7ppa3YbSNcJbwNAFUu+FFl005SpGT61Ty4iLUDlBbxcVYIK1ITw/U4sDvc6zhrXg6RVrAx9HbcBQaFFDWuSqiRUgoRDkqLDRnfEo26NSKl6ErJUq/BTh9qLLEuS69GQnBt0RI6fwrMw5bqnVxq9rJR3bNLa3p4QAPywe0we/PXE2hgZcP1DK/RmyMgiqBLmcrpUqC1KwPgiapSrYL/GqHI4p4j3MjbwOAHhGjkE6ZscSlrsgTXHGyJH3WnYeEQDBs17nI40ItgaYU5zZk7PXMp2GEqBaJBDxoYCKKupsFuMRYotciVHGyDmSnXj/9sbDp+GKvcbjdyfPCXRM6opmvsxzzQd0sqikiaMUUCH5+Y/sLFz0sg1qJsHKgSxy6u9M958adGK0+AQA8HGm8CBaP6gW22HSkTti5BBXptan78WhrT0ksAaEPit+3B+Pmz8MAHDBMltj6LDMK7Ly0bbDvvz8LHwdRLw12fncwKm7jLvAqr1P7tgEN2GnpO1xKos5YuTs7cUQmP24QXtBXStprEkmoNBDx42fZTN9nnIKcsRq0+FTkNtpdBsimm5V79dg/6ac5B4hBOaN7O2oLQfo2Qyrohr2mNw/bxvdWWKlGFhubgpBrjOEa2VPZkl2l315NjPalzXLi2LXHg0KHSuqdS+lmMlOwkB75RkjZ8wF1Ug4LXIKQU51r6rInNwQMoM4W+RKjCpGTigG+qzhLXj6A13j3lIXx7Hzhwc+ZjLtYZHLMSE4TMxlPnGXGro4PWbeUPz3bb0wt8qqqfYbz47zyDVpU9fKydr7AICXZfCxEYaY4hxUPu65zqOTuC51IaaMdUkpYhHLiTkj7IDqmnj+qfaS3cfhgGmDML4/qT8ovMcKPeMqUuQ5rJul0hVNcWlVluQgd0KVpMZPkiCKJkQo61JPZZ8rJ5RWqyJcCnUtwtyNJ2QMEIBMdSEC/d2kuycF6xS9n37i/1SKUzfUarPRZ32zAU01eOi8RaiOa7jj8Q/JccqfXcf3xatXLsPLn6zHP15emXPfMp16Lbwscq11cVQnzBi5HBY51fYePGd3bPJTmXFYrngn5KPU051TcULOQVGmp9RrTXq9vNYYnaQ8RBT561+qjCCNtXEcO28YPt/QiT0m5VeeeLYd6ldM0fDzMqED6sbDp+KMxe24/9z8QeYqtnQRracZI+ezj6V+uModGiPXq9rW9tF8HH4Wql6CtZ/MarWiC+PERwCA1wIUA/fL5XuNRzyi4bBZ3sW5Kcq4wBxWo60kzX1CxpQLMpp5tdguGMVi2pBm3HbsDNzzlflKYZcSi2iYOLDROeE7FDr258NmDUF9VRSzhrc4khaEFWrTjrhZekyVoiH/XBXkmBSqifVXbyjcOW/r3gV3njIXu0/qh2/saae6dp4xTWpT+PGU7rl52jZdF2Wyw1oQZUIsTejYVwn2zrHtr13qWunXXV0AGNJaiz69qn2FSZQbsYjmq6/lvh6w3NxIspPOZNpXjJzq9IPON4VcIXfZl3czA/NaitT9KO29os8nXTI431/kcxm913NlrawWCcSQv2xKLqX9FXtPwE1HTQ+d4IUFuRKjKjPgcKmima56VeOCZWMxso+/wqRevL1qc85+uHFkkauQF1GpUGWtdAgeWv4YIK+HPqdLouFaOUKstMoPvCmLnwHtuPnD8eqVy7DbRFtzpJpwla6VOcYQ1XgnEFMuDlvqbE3qkBZ/WvJSsPPYvpg8qMkq8RAUVYzcoOYaPHXJLvj9SXOKklVWJVTRY56ZOEP/MHZPtQIiwGIhrVhsB10chp2StvWZbNbwFvzkiOlo72PH1NDFOU1sMWGAswxNGMKG3G0xFquyaxM0wyKXCrE0oWPfT18cFu4cg8EhyPm0yKmEt0p6ffpR1pS7IJf0SHbSlcoQ18rgFrmePOUtrrIvq9Ac+vqrPL56CtW7zBETTQW8ErtW0hHgpSA1M2zXwPYkAHJY5FTPUyFdNPtXhDaYAhCKwd1Tk78f10qHIFfmE3epSTkKgtvXjS6U6YJDJQR5bfVTR65NbACguyZ9IMOZ6fMRj2q+3G1VcWG5xtCrchgOxn8BAB9LdW2jEW31uPaASYhoWtnGyFG+sdd4fLq+A3v6iDuhqLSvUU2z6lM5NJ0hH0+VIEebuyczH2MWHo8zFo9E5BVvl6viWOSCLcjDzo/bS/kB95hYMr4v/vv2ahw6awjmjGjFijVbkc5k8NyH67wb8InKep7vHlo1CjvWI2oITWHqiNHT9ONq6/SGUbNKNpP9pKfbe1ZfhPczWUlvT1VfBbyzbpcjaSODYGcigWroCtVURqIqUkj5gZ5RNAFAi9jk+DuNiHLNmLcf5HMp7psqNIAmYKJK3nJaazbWZgv8tmtlElGRv2yKylumGFZ6FuRKjCpTJaVYVrC6eARbEmncffo87P+TxwEAzXX2RKZKrhQPmHxgWyZfAqp0xtvlL+mwyNHr6f3Qe93ynFkrXRkeP5D97CQCgK8VRJDkWnRMqiYoVbByrjH0WGYi0lIgIiSez4zKudg+ZOYQX30tB/o2VOMvZ8wP/Dt6CWtJ9jvqnkqvc9jnU2Udc49D816rxmKQo/uJkfMzHgMtZsgYL3bWxnLFrQm/+cjp6EimUVcVRXubbq279ZH3Cz5O2Kv5JQxr4NY1iEBP0BTKIkdj5BT7OEtreCtO3bwv++P5zEj0E2vxUGYqNC1/TKYqxr1SXCuB3G7V5vmX+3rAtI68/skapFesteKPq4Qf10rFufXgKQ8SX1ifn0iPzzp8EE88R4hMKQQ5hQBKFb5+lNzFJqoJZeItk+PmDcO7qzZh2tBm/N2IGzUFuRrRZblWJnLE9uZyrSyUUtsut3v8TPLFmvyf/foSPHrRYkwb0owLlo3B8N51+NY+dvFNP4UZy33i7m6WT8yd6l5lkUspLHJB5qpcC1a3ZvHtEG6VQe6s8KE5Uwl4uc7jPTkQRyYvwbGJC/AZegfo0bYJdVVsqLHvcUwRSxBW06rOWulsz7zXyoVAEaaHoC/wIOfscNfZRuS4fFOy26VK04RlzbW398y87tXXL6UuyL3/wQdWjFwsGsP95y4M1DY9BaWcpYhVzoWEhv0TV2LHrhuwEXW+xqcq63QlvT6Vj7gPb4xywVQIRJDBTx56F51JfXxVGYngw7lW9tw5m0XBH0xPwWHJr2cdP6gSy/6jGL0Lhir7eZwk61LlD+jOcdZcl782ZEtdHI99bWfcePg0a9tGqXsCNWGzNW+pioEDOc6hCOOpYgQ5IcQoIcQfhBCfCCG2CCFeF0J8TQhR5dpvnhDiUSHEViHE50KIG4QQWY7tQogqIcS1QojPhBAdQognhRC7KI7tq80wqCZ56qZSrDFcE49gULPe7TMWj8RD5y/CqL52rJ3qMA6NSXnP293O1ftNwhmL2/H3ry7w/J4mO6GLRrqdCjgqq5VXrFEuLVrCNYF8JludO/hyUfN/c1VuEqp9/Gw3eSIzAQ9npvruy7YMvSX1ZPFNr6HDUhfyAc31M/qdOXaLESOnwulamX/gBnkP0kX4tmKRy/fc+lnsFWVeDxiXZrJW6u+grRu+sGJNqqviGEli+3wdnhzfz72l1gw/opnp7ukndmdbiJHzk+yj1IKcqo+txuLcvGdRpJFIZyzPg2qrjlwY18qAfSxgTvxPZgZ277oaZyfPsNtTWHvzMYCUmagJWde0WNCSF3FFWYRYETxN/OCnLIMQ2fOs6XJdLzrRBD3vhKr0AJDrnVk4FSHICSEGAngawGwANwI4B8BzAL4D4Fay3xQADwCoBnCu8d0pAP7g0eztRju/BnAWgAyAe4UQc13HDtKmb8zXjHOS93YN6ansaqo5QaUx2R5pqo3jgmVjMXGgd3IAR7ITxaLRUU9F8QR63YvcAflx19+uF5SP2xbkzjoWQYqOqVLhb+9jKAjOoqTebicX7TYWvaqjOGTG4PAZHHP8zmF9Ne6p0rWyCLeWuhv7qgcW4KAOITFIp8qYfI8Tfd5UAk4xspCqjWBUKZnd4Bro7m6tYqMlyEmtsKgPlRxH++KYt0IqA/wszvyWOSg3VGOinJKfqUr5XLH3BAD2wjqKNJIpaY0L0yKXS5ArVtbKQm/563KYI1tqUIvcNftPwvj+Dbjx8Gk4ZacR0ATwkyOm5f1dd3DJ7mOxx6T+OH7BcGtbXGHhjkW9333Fxo8g53WdaezsQPElADjDWVyoXSuLoPwsuIWe4UgATQAWSClfM7b9TAhRA+BQIcTxUsokgKsBrAGwSEq5GQCEECsA3CKE2FlK+aCxbRaAQwGcI6W83th2B4BXAVwLgOb299VmWJwTvvf2nkJ/sWW/AeOK9LBMNilFjBxdQPmzyGWTSwDqkC5BzuX772cBEWQ+obXLaPwfRV1awf9xtnfotaIuznQMjWirx/OXLUEsouG8O18KeRz1TdEErCo5lkWuCBm45o9s9dwe9KUdZHc6l20jBjnlvG3i9PTIvw8lpmlIKJ5vN36sp1FNoMu1bZ1hkWvBJkTMpAEi+HuGCml+yg9EHAKWf6iiISIE0h7X3mk1oV8EOFCJUcbs+8z22RNENIGk4e1C70VTbQz7Tx2I9Mu2IJeW0hoXfmLkVDcr6CkX+xI5XVvz73/orCE4dJYeT/615WNxzpLRqC6RRe7kndoBAE+9v8bapvLuiWo9ozCgaxkVXodfhWZ0ySiqRAqjtE8BqDNWAjnemUU4tUpZlZsVcle5tn8OIAkgLYRoALAEwB2mwGVwB4DNAA4m2w40fmdZ86SUnQB+DmCBEKI/AARsMxjG3K9OL257bm4mdd+6E9V4ohoL1auajSw6NGaWugbQtZAf1xSvhXUuzY1ZENzE7WrpZ7IIoi2mY0K1aCqGFq3UC4VSowoKd48PU0sesgxNzufXKx5SHT+T/4Y9feku+PkxM/Cr42d7fu8n2UlUU1+LXNDrua24Vl6yfCwAYO6IVhxmLNj2mzrQ+t7X9VHsE8R6rrTI0dptHu2Zmu1a0YUW6Fn6pBbc5Y0eJ2j5gSA4y3147+OMkQsnMJYaZcx8Gb3sHaV8yL3QhEA0IqyFdQQZZCS1yJmulTli5AqY47oTlReX39+WSohz98OEWng1xfZctWcLpSoWziKXgYaPpZ6cqV18BiC3IFeMBGEqKsUi918AlwD4uRDiGwDWQreaHQvgWillRggxCfr5PEt/KKVMCCFeBDCVbJ4K4E2XcAbo7psCwBQAKwEEaTMQpvZQc7io2Z/b+9ShKqbhy80JzBnurbkuNqo5wbFoV2T3+f3Jc3HW71/AOUtGd0fXKpKYQtgJGyyea9eOLEEu5sjG5OsoAWYUP/1WTZBBJq5yT2/d3ahebCohxK0t9yur5HStJJ/NRVxNXFUrJ/+x+vSqxi7j1HX1/CwUYxENqUza9zG92EbkOBw9dxh2GNyEsf0aoGnAXjv0x7QhtttPITFyQRbtvkpFkM+7TeiHf732OT6XLda2wWK10aEQgpyjLwqLHO0L9YAJqQxQZnZUWK0qaT5T52YgihbH9p5/ptwlWWC45groHgxdRvmBqEgjkyEWuR6MkSs29PCtPhJ1lCP0MaB15JwCHlEgdqtFLpwgBwCrZRNG4jP0E2sBAAmZy7UyWNtBqAhBTkp5nxDiMujC3N7kq29IKb9lfDYLNHkVOFoJgMa+9QfwqWI/ABgQok0LIcR6r+2ERtMdwKFdcWnxfnXCbEgpezCjWH4NnKors4a34ImLPXPFbLfQ65ZI2SY5OnEEyzql3tddfqALMUSoIFfkIeTHxbYYmr9SvzRLTUxRZkBtqbL3iUc0dKX8ucXlEsy9LMhTBzdZGVy/2NRl1SArxlzlsMgp7DyxiECHvhYLfcxtxSKnaQJTieA2r92Z7VWVRMu5j8IiF0ATrrpXFOoevHRCX7TUx/G7pzJIyghiIo1BliBX2NyhyiYuFbHKYUetH1fVSk12onQtpJvJ+QeZb4qFsoamAGKawBbD6SyKNDIS6Ezq/fMjyKluVXArWO7vI5pQlmLxgj6r+00biHtf/RztbfX4/TMfYWsineOX5QNNtkIzejuUHj2UtTKsayUAfGnF9+qeBGFcK4uS6bnwJnqMDwA8DODP0GPW9gBwpRBitZTyJgBmGhy3Cz4AdJLvYXxW7Qeyb5A2Q+HU7mV/35NmfNWR6IOmyjDEZEMtKIvGtOHx99agqSbmKGCt0nj7iTehZLlWyhiiETsexU+WqiAjjS7wVC6ZdKxQbW2QMV1JyQG6A7rwpUKdanzEQysJ/H1nCopCCPz0yOkAgINveoIc0/chlfhREugJmFKBj0mFN5o5bVuGLoJU9QJV1zCIJjxozT8hYBSX1rAWvdAX69FX6AqBgl0rFUIl3RoJKWDRtlULcNV7vZLmM9WYcF5nm3i0ZwQ5TdiCujNxmFMRHo1oVjr4CNJ45dMN2PUH/4WGDGJGLGYiZx059fG9CCqQmUQD/o72qyoawS+PnwUA+MMzHwU+dqmoVnjreGVIBkqftVJ1eJrwBAiX7KQYZ1YRq3IhxKEAbgZwopTyFinl3VLKEwD8EsD3hBDNADqM3as8mqgm38P4rNoPZN8gbVpIKZty/QOwwTo38rtSu12oFth0kqELodMWtaMmFsGtR8/o9r5VIvTBrY5F8OhFi/Gvs3dyLLZVGu8tATVrbtfKLsSgaQJ7TOqP9rY6HD57aN42ggw/Py5XVYrkHKqSG96d8t+nbZEYuUCDW+y42b4N3q6JdMwNavYWVL5mxFSdurDd2kYtOm7yxXQ63TmLYJFzCKze+2zoSNjHDDBIupIZfGufCVgyvi/O3k7cwKOKWF2K6hoGyZjsL8Oo85jmcFkrdc22KcghEkbHTN9T+fdWecPkg7atzgJKP1emRc5Pv6lCKR42QDcgdDw7vIXIPgIwYuT0fWOw36dxwxoH5LPIqSySCus12d5cq7fb1str6egkaMxhsSyFpcQR26h4VlQFxItNlULJrbKqU1bLJsffYcoPbDeulQBOB/CclPIz1/Z7oMfJ7QDb/bE/sukPgP52ZY79QPYN0mYonIOl0NYKQ3X8plp7sqP10E7acQTOWzLaYTVgvElnJGrj+uNGJ24/2iA/dCFmuScBerITTQj8OECa4SCLGX8xcvakRjPr0eNE82TF295dK+mz1d5Wj6v2m4h4RHMIdZTpQ22B7Cs7j8RZv38RB0wbhD89/4m1/ZSdRmDp+L4Y1lqHue2t+OfLK/G15WPxt5e8pzOnRS77hkSLXGfSz8ImSeahIMfsSKZx1NxhOGrusBA9q0z8PKvKDIVFfim53WbNuWC91GvGNQsjbF0rLPZHWX4gREHwXG2o5EWhsshV0HxG+xqLaCQ8wFtgVpWbKTYRkkY34ph7nAqlmKZZrm5NYgt6YSs2odZyqwSyk4I5jqNQsqqGjabB6tftx83CA29+gYOmD8LSH/4v5/noc7x/xa1KqKigoeV4Z1CPr1IYM1RrMD+xsBvhfA+HKQi+PWWt7At4irqmhBGFXjogBcBhHhJCxKEnL3mRbH4RwFghhLviqJlG7SXj/yBthsI9+RSbWcP1QPIbDp2Sd1/V0c9bOgZ9G6pwysIRDutcPKqxEOdC5TIwvn+D9Zlqo/afOggAMKDRaWE5YvaQgEcWWAe7uHvCiJEL1EKA3f0s8OgESc+P/jRfavNKckXqDqKOxYTEEbOH4qAZg5X7Lx3fF9/ZfxJ+f/Ic7L3DAPz3gkX47oGTHfsIITCirR6aJrBwdBuuPXAymnMEzdMeeC1unLFGRbDI+aj1NmGA/TwFcfdOhXB9qnT8xDgrY+QCJTvJf23pcaS0+7OB1MkCABkNLsg5s1Z2o2ul9PZQoTjaC2n5KzX0XlHvCpULa7QbMwtSooq4YXeip2hEOCwmV8R+CQAOQS6XRU6dLj6/Ra5/YzXOXTJaqXCjxAJeNz9j9Zi5ugdOc21wF+WegM7Zj7zzpec+PTVTq94fziRF3r91l6/IGSPXjRa5SlmFvw1ghhCi3bX9MOiqjJellBsA3A/gKJeAdhSAegB/JNvugi4EnmhuEEJUATgOwGOm5S9gm6FQTQqFDOJj5w0DAOwxuT/+cPIcvHDZEuwzZWDuH7n6MnGgvVBqb6vHkxfvgouXj3PEWBTLmlSp9K7XFxtVUQ03HDoFI3rX4TcnOlOq/99hU3H8/OE4dv4wa1tH0ta+9WmownNf3xX3n7cQh83SF+hDWmrxzX0m4jcnzsYLly3x3Z8vpV2kvAuxwNYRuvvpi/RH7WLDDc8NHZ/11d5aKGqRu2T3cZg+tBlfWz42WIxc5ax7uoWYjwQnFCEEDps1BHNGtEIIgaGtddA0UZClzJkZLrshaqUvxv1yFO1WnPQ1+0/G/lMH4toDJgVy/9se8ZPUQxWWGESQ8yMj0+NkpN2f9dIpyCGS3yXNjZ/C5xTh6Iv/N64zOybw9T3GoXd9FS7dfZxju0maKKvi0coZqw6LnKIEET1PZ/bB7usXvc+quUkTuoXwIyM9PAC0Cz2/XbORmAKwLcFeqDwDcsXImQRJcBNU4apc+JPN5y4dg9euXIbnA6wfehJVghE6P1CjQdCcAcH6Yh907x0GoCYWwWGzhrjKhnhf84RLEZCUOcoPKBUDQXrrTaW4Vn4XwHIAjwkhboRefmBPY9tNUsovjP0uBfA4gIeFELcCGATgPAD3SinvNxuTUj4lhPgjgOuMmnHvATgGwFDorpoUX22GpTvWIJfuMQ67TeyHKYObIITIqW1X9WXHUW34xp4TMLhFj7MxJyb6cJVTPZlS8IdT5uKnD7+H4+cPx/gBDZ7C8l47DMBeOwxwbPv3a59bnzd1JjG6r25Ju2zP8Zg1vAULRrYhognMH+nMPpePzbCtXgkZDazpoS+f85eOwYHTB2F47zp85943s/Ztro1hp9Ft+Gx9B/abOhA7DGrCXjc+il8cOxP/fu1zjOpTjzjRNPbuVYU/nTYPABwufEfOGYJfP6kO0u7OtMOVgLOofPh2hI/c4HvtMAB/e+kzXHvAJFcfnJkw3Tz6rq1RLUZQOh2HLXVxfLk54bEP8INDpgAAfva/9ws+5raMH5e3iEKS606LXIZkZF5PvAn0Awe3JNDz9POo0LklyDrRLfSduOMInLBgOJ7/aJ3n8R3JwiKlr+HlF1UqeHqf6aVw1P0SAqk8F3XCgAa89tlGxCP+i84DOeKoXGkrYxHhGFfPZsYAIO67gMOLJes4AS0o0ZCCbNB3nGpvul0TQF1V+S7vqedSc20M67bqVlIqMFGjQXda56hQ2d5Wj+u+MRnVsQi+8tvnre2qW+S26IZJdlIMKsKkIqX8H4B5AJ4HcAaA6wG0A7gYwFfIfs8D2BV6lskfAjgJwC0ADvJo9mgANxj//wi6hW53KeVjrmMHaTMw3bFOjUU0zBnRGjj9u3BNkLOGt6B/ozNhglP7vn0vstvb6vG9g3bAeOLm5YcdBtmWs8mDmqzPtfEo9ps6yFeAtBc0iPsj2Te4ayX5rGm6+53SH18I/PK4mfjPOTuhOhbB+AENeO/q3bHT6DZctd8kHDt/uNLHnH6+Yq8JuO+cnfD1PcbBi+3d2kK1hckAix03fi7jDYdMwSMXLsYhM51uvfSnXq7UY/vZi6FixcmcufNIzBregtMWuZ0wjD4J+nn7HiP5cLuceRHU+uCFMuU/7YtDeLK/2eIqn4JogRY5df0Bz/2DLBS92hZCKAt/03jOSsr6rMq2SU+f3sNY1HuOV3HTkdNx6sJ2/PmMeaH7RYm5BCnT7fKetF4lqt7ITVdrJCffKquQybEEDipgOa+X92cvgs5fyiL0PZQcpBhURSM4YJoeVvLIRTtb2x331kdSoWJAn8lUJmOtmzWlksDGbZELU35ge3KthJTyaSnl7lLK/lLKuJRyjJTyGill2rXfo1LK+VLKGillXynlmVLKLR7tdUopLzDaq5ZSzlJZ2Py2GQb3TTQ1Ffu4rDg9gVuj40WY9LqMkyXj+1mfC1n4Xr3fJOw6rq+VffC21O7Wd6vRFHyCCLq7EDlfQtGI98Im41pMje7bS6mRvWq/icE6VWFcd8Bk9K6P49cnzPb8nipjOpPhawT5WSxomvCM6aA/9bLI3XbsTIzuW4+r95uU9V1Yzl06BneeMhcN1d6WGbqwLO8lS+nx4zmhUvoEnZ9mGMl25o9s9fyeLohojFzavQCKhIiRU3x2NOtDqM1HRgI/PGQHAMBfz5hvbafzLX1O6HxXWYIcFXS93dxUyU58VBDB4JZafG35WIzorXZvzNcvijuDpWlFXGe4TzYJfclWaxTlcZfsyTpOQIucKt9BvrnXz7WiKDPMOpRbwdosBd8/eAesuGYP1BPLodtib3/uvn74cZVVxsgFEeS6MdlJ+dpetxPcD/lD5y/Cqo1dmDK4qaR9UU1i22OygGKz28R++M7+kzCufzBLnpvDZw/B4bOH4Ob/vgcA+HtmDhKJKF6VwwGEeUEUF1X66nQm26rblXQKcjccOgXThjT7ChavZA6eORgHzRikfNm3ELfoKUOaQh9nUHMN3l8dTvdEFw4xjxifAU01uO+chaH7lgvloomM7UpYtJQSPzUfVcJeUEHuir0n4G8vfYaTdxqB6d/O1ovSw+gxcvqGlEunLENY5FQufxQzczCg1pCfucso/OiBd5THSWck9ps6CPsZiaqs9mi8liKBRSUJcqrHyikwE6WcwuUxH0GTpDit8fZn58JbWN4Dm4zMgr2wFQBQK3SLXFLTQxF2HtsHD775BdzkzE7pgbI4eR7oHBeLCIcF1wtlhlnX+VckinWC0sJelEPaB500sJFst1GN5w7pVDiFEuSKsPJiQa7EuO9t/8aaLHfGnsIxKSoGbjrT/QU/t3Uimp6QotA23J8z0PCvzCx7e4knc9WLxWuR5S4kWxuPbvNCnEkujW11LIJ/nLkAGzqSGNsvvOD/f4dNxVd/9wJO2nFE6DaAnksxbkIvTVQTliKpkrL/lRo/WSvVFrlg13niwEZMJIshNyqNuztttwhjkfPhikXPx+FaSfb/6s4jMXNYM55dsQ43eAh06qLqVJDzfk56qtZaMVAmYpPen90Fuf0SNNZeJaQ7PECE3e5GaQhywhDkDItca3MLrtptIvacPADvrNqEWx55HwtH98Elf34l5zkoM7wqFCb5zs5tyU2mc3tebO5KBepXJUHPYXTfXnj8vTVIpDOYPrQZ972+qluOmZYSvzphFj5e24El4/ta25NEeKwlVkNa+H0znGv1dC5XXcU4L8aUUDmzyjZKOT179GXGFrnyxrk4K47vdbHvrOoF7bXISrgEuZUbOorcm8plwoBGzGsPlvjGq40Hz1sUSoHgcA3r4YUoffnVEDfTqA8rU23cqCFFUnBXkkWkWER9mOaL5VqZD6e7nv3+c1vkvLJWHjhdt4Bd5yqnYbeXvx4VTeqimjdjEQ07jmpDL0U2XpV1gB6fJnpauyVBtlfO+KNDQlXagV4KdeKR3ASNEaPzkSOun95bCGvsmha5BjgFuUh1HY6YPRSNNTHMGNaCm4+agdF9bTdP1SmoeutQnAY4JbprzMf89PmGTs/tfuqelTv0mkcjAo9dtDOeungX9FK42AehSVGKIZXOYMdRbTh89hDHeEqSNUkteffce9aOOHKO/h7dIp1lo7JcxAlcfmAbptRWEwrNDqcaXN1p4mb848eNI3CikCLf2jVkAUMTdXgJcu5EHmb9Q6b00LvVU7WiTKgrHO2Hn1TnT3xtF/zupDl4/utL8NLlS3HZnuPLNh13d+KOHfJCNd8XW/B1W8HMv9wLIGHUkaPduu6AyXjkwsU4WFFHUQiB9ja9jMEZi0cq9vHu146j2rK2qa6JyiJHE4FRAXjakGbrs0o4LEdUApbq/KOR/O+kYqBKS++2PJv92WiUtmg0Y+QM10rEXCUv4C+2zY/iNOz5+1GcUKsRxU9MV7lDr2E6I9FYG/OddT0f+ypKcKmME3RNQtdSo/v2wjf31mP3t8IlyMngFrliJOtiQY7xRDURbC/ubuWOH3/4oNODSo4zNeCqzJIq6At3/VY7o6bXOiDlctltqS3O5M0UjirFeE9QV2Uv8BOOelz5+1ETj2Bueys0TaCxJoYTFgx3BNZvLzhc3gJqhYtxv1WeHpmMtASrpFuTbcTIRV19z/X+EQDuPn0+fnPibJy8k7cLsWpOPH/ZGJy580j8+XQ7g6JqfbXLWO+FNJ3DqGvl7pP64doDJuH3J8+pqCy8Dosc2e6M4fK2gnanRUiVcC2W5Vqp34MvjKLgzWIzqpCwsleiKjvJCu222rXS/qyqaScCWOeCejwMavZ+Bpxxw5UzzgC95jEAXEUSZuWLFfTLNftPwm4T+uGsXUZ5fq/KBr1DjjwV5uXd4hbkcohUKg+lYoQrsSBXYpJlauFSaQ9uOHQqJg9qxPVGDSemNNBhU6wMoyrf+4NnDMbLVyzFiQHjq3YdZy94RvaxX5peGl33pK0qMs6UAm9LQ09QRyxy1P3Wz4KngtbMPYZKCFHHbxR+EaXD/c7+nJH2gjPlLqRrWOTyHX9UH+oKpwvs80f2Dtzv+qoozl06BlOJ9czdwtX7TcKRc4bgakUmXTqHxVyL+kNmDsGcEd6ZPMsVd4bRaUaypQuXjbG2O1wrQ5Zz8INwjRurj45EIU7XSrM/n8O+p8u0ZzFCrNT/qLeLhXu1p3StVOxDXR6DjD56rfLFpB4yY7D6WS2CRbBU3HjYVLx0+VJrjAHAuP52WZtC5NJDZw3BTUdNd1j26PVRrZOOmTsMe+8wwMpQS9HLjeieBJ3SdtlMQ8PNR033bE9Vq5MqucPCq6USk0yVZ/IQlUZnTL9euOcrC3q4N4ybqWTCU2l5g9ZeOWj6IPzxuU88v1Olgc/FgKYa3HL0DABOS65Xv9wuxjUBayAy3Qe9XT0d40Ozdo7oXYf3v9Tdo2gsiap0RXcWYK007jtnJ3y6rgMLRnnHWirds4twCenznhUjZ3x212MSEdMipwHIvr/XHzIFv3xiBb530A449GdPYvWmLhw7f1jevgRRbrnfgbNHtODw2eoY0xG9bVc9qriqVKgFISMlfnn8LLz66UbMGt6C79z7JgCXtbVIVqA/nDwH1/7rTVy13yQsv+ERq21TAUjvIV0bu92tze5/IW1B7kfxG+0f9Mou8UTPQG29JvsLAVMU20QUoQ7rnGcrNo75VeFpMGFAA05b1O5Qjmb3K79baLkiDCUMANx81HS8v3oL9iYluPyczYkLhuPWRz/ALmP74AGPLKSUWESzEqypXCsba2P40WFTlW1oQiAjJbagGtVGDd/BvRuwaIJdXkoI+/6qhPTe9eHqBlNYkCsx5Zo8pIdDYRif/PqE2bj7+U9w0fKx1jbVC3TFmq2B2r56/0lYNKaPsgZUGLz8+b3ky9MWteMPz35s/V1pL6JtmSAa42JTVxXFTUdOx6qNnXj9s42WIEcXbR0J7yxvPIZsRvfthdF9eym/D+pyGQSHBcVdtNv4M+HOWlmnx6ypYjL3nToQ+07VY17uP3chVm/qxMg+6vMz2Wl0W95Fnok7AVNVHnfePg3V+NNpcyGEQJ+G6pz7VgJUGEmlM+hVHcPcdue7QVViRgZUIlJmj2jF3afPd2zTrR861KMjorDIaUJYY60LcayT9WgWmx1tiob+Wcf251rpLaSdsbgdP35ILwWUb6yoUCUmaq6NY8/JuWsL93T8cnexjAhCJn6moUv3GIcDZwxCe1s9Rl16b85941SQUygC86EZQvxWWY1WsQkAsgrMUwWEezzNHdGKZDqDXcZlW4aDwoJciVFpk0tNJfnyb08sGNU7S6terFsVi2iWr3p3cvqikbjkz69gRJutwR7Wuw6a6N7Cn0w46KKsFFau3SbqL/YL73rJ2kYFyo4CCqUzOkFTrQeBWuTofZOQVsZRtyCHekOQ8zHeGmtiljY/H0fMHoKIJnzVaXWPq6pofi+B6UO3nSRNMSJUqOQyKjzRRGjFnsY1Yvmix6HKGnf5ASrkuYU4wFuQ8+da6b3/8on9Mb+9N/o2VgdSItFdVVkr/XjXVGqmymIhhPBdoicW1WAkL0VnMqQgpwFIA5tJnFyXcFrXqALCcZ8jAr87eU6o43r2pWgtMaEIqw3obrb3SaGSqDTLw2GzBuNPp83DX89wal17Ov6K8YdXAfdSQNcytB+pIgXFb8+oBKZi3G5632pitsC246g2q/0s18o6XVlVbMVBNKLhyDlDc9a6M3F7y2xvpSuoMleVqbIqpuXdpyh9oc87da3McnPUiUU0x29uSO2X1aZoyG3hUiYRU1ghNSEwb2RvtLfVK/f3bI98jiusan4u7Zufb8q/U4UStG7obcfOQGtdXJnLgd7b6li459psg2au3Kg1eu4DOM/BT0mYQH0pamtMYMp1EcKCXOWgulcLR2en1C4HhBCYPrQ5qzbMmH75XaOYnmdjp3cSnJ5G5YLy0yOnIaoJnLBgeA/3aNtBNYeoai8FIeNKEf/AeQtx16lzMa6/rT1PSJdrZa1u2SpleR63kjWsu9y2gCoEhLo4O8sCFPf4Kqu7KuV+VVRzxM/9MHUQTkmc4/xxr3AWOYfwSLaHHarOWnjFiXff3tl5bF88+/VdLffrbCTO2XU0xvbrhXOXjFHskxtzbqK15DblEORonUk/ngZB2H5npjKhfLNWlroHjF9Uc0KlaZBPXdgOADh4xqAS94QpR5ZN6IefHDEN/zlnJ8f2HUe14aXLl+KS3YOVx2BsVIvQM3cehb4NVQU9k7SYfW08gva2eswYpgtq5mGTLtdKraYJABApYdyPOzFKJRXzLjaq+rF0oTq01U5oVUiMXBColcNh2YpqWUqAf2dmOH9c0ww3DkOJD3fjtMJt2NHHPEOYfj9JYSn2czn/eeaOAIA5I7Yd99583PMV3avn2HnDsr7LZwk9a9dR+NfZO6FfY7h4Vq8SBJuEUxl9EJk3Hdl7izyvcYwcw1Q4Ki3esNbKqvm3+6T+ePSixei7DSQK2Jb46s4j8X8PvlvqbkAIgd0necdw1lVFe2zxuC2iWvP0aajGkxfvAiEEVm7oxCPvfImdx/bBgyRhyD/OXIDL//oafnzENMdvf3HcTPztpc9w8e5j8dpnG/Dm55twtGvBpXStjNUAKL4LUhDcVqjtOW5cZZHLSImr95uElz9Zj+PnD8evn/wIQPFj5Ia21uLDPMm76MJdt8i575dw/yCrDVXMn6oVKuzHI94xlPlGjQBwy9Ez8Og7q3He0jG45ZEPsvbxY5EbP6ABK67ZI+9+lYhqfhrXvwHvXrXcUbexpzDH1yZpr7M2abqXwSMXLsbbqzahuS6OO574EIDbM6G4/WVBrsSUq7tGmYbuMR64NU8n7zQCr3+2EacvGlmiHoVHVeyUKR1nLB4JIQTmtZd3HaxKixUtJ6j14qLdxuL2xz/A/tN0bbJ5XW88fBr++/ZqLB7ThklX3GftP2FAI+46bR7cLB7TB4vH6O6wvztpDtZsSWSl5TctKl1uQc5Y6JSyhETQOpzbE+P7N+D1lRtx9q6jscfk/jh89hCs3NBhfb+pSO7Ydxw/C79/5iNcvHwcdrzuoZz70pFSFY14ugvfnlqKY6P34erkYbjEow2Hq6hCeKLzjEOQC7mWG9u/AUvG97UyPD9y4WI8/9E6nPX7F619VEWrtxeoIiGiCeu6CyCkEFf4vGLOmfdlZuBg/BcA8Gl0MAC93NLgllq88skGa386VortWsmCXIlZPjE71WqpuO6AybjwTy8DcPrzMuWNe044ccfh6NOLrVpMcaiORXDuktGl7gbTjbS31WPSwEZs7EziuPnDcOrCEVmCcWNNzFHbKQjNdXFHQV4T8xCbZY3n70oZI7e9L55zcffp8/DR2q2OkhbdIXTvNLoNOxmx3nXxCLYk0jhrl1G44YF3cv4uFhGeIQdXpI7FFaljAcBbkIvmt8jRdukuKkFOpWC68fCp+OcrK/GtfZwF5k0hgApyWxQlVrYX6LNYG49YioLwyrvC17fmse/PTMP5yVPwTmYgNq137kMzqTosckV2rSxPc9B2QH1VBN89cDL2UwZj9jw7kJTMQbMEMaXDrXn0m4qbYRgG0N2E/nrGfDxw7kJUxyI9Zt00j7IZCkGOLXJlSXUsklWXkArdqlqk3z1wMqKawDX7Twp8zFeuWIZ3rlqOQc32WMllNQszdqhFTuVOqkoM5Mcid/V++nl/a9+J2HPyAPzkiOlo8VBwuHn3i+zyCdsTtKZjfZVtfyrlKtUeKgJ3pRfiJTnSqnNqQuMmk2m2yG1zaELgoBmDS90NBzGF9oApb+ic0FgT81XviGG2RX5x7Ewcd/sz2GdKOMvR9oymCWg9vTSyUnhXeX5dyiLHtXF7eVRpiaNKAXVxWzi6DactHIkRbXWYd82D1vaDZgzGXjsMQHUs+DvKHJ90TFDh0Z31OEzmbdq2agmkalaV7IRy+OwhOHz2kMD92t6hFrmauD12SulN72d8xRRZXYsd08eCHGPRVGtrhliMqxzohNKnl/eCiGG2BxaP7YOXLl+KXlX8aqsEvHMO2hw0fRBeJnEmPclpi9px22N64om7PWIAGSe1ZIE9rLUOC0b19tzPS4ibPbwFT32wFkfPHZr3OMsn9sfN/30f/Rur0VwXx9Mr9O3HzBuGlRs6MdPIiBpGkHMkO/ERI0dRZTUthqxhZmfcXkkQaxZVVJcyLtprfN19unOeiCosvGyRY7qNlro4Jg9qxNZEGgdMKx+XTyY3dEJpY0GO2c5h1+LKId9i+/DZQ9HWqxqTBuUv4F1s2npV4Z2rliOqCU6k44NYRMMNh07Bh2u2Wok7/HLrMTPw7Ip1mKdwyaRUxyK496wdIYTAp+s78NCbX2Dx2D6ojkVwxd4TrP3CJAakgpwqC65qDd5dY2TiwAZMHtTULW1XCkniWlkMIagYdZLp+Dp89hCcsXgkBjY5XcSpcE/PQZV9OSwsyDEO7vnKglJ3gQkInVBYkGMYprs5bNZg/O7pj3HVfhPz75wDup76c3o+9os8hiMSF+M3xraIJrBbCROCxbbj2nFh2GdKOAVwr+oYFo/t43t/U2ga2FSDZy7d1dNVbf3WZOB+0Lg6lVeScMUCPvbumjx9DdwNAMDfv7oAv3nqI5y+qD1cA9sQ1LWyGHGzxWiDCoO9qqNZQhwAVMXscZlIZ/Cn0+bhf2+vxgkLhhd8fAoLcgxT4QjXhMIwDNOdXLXvJJy2cCSGFFirkq6nzkmegXOSZxTYM2Z7QxVvVKjVRVWcm7a646g2nLnzKAxuKX7ZnIkDG/GdEElhtkWmDG7Csx+uA1Aci1wxLGI0PlM11qqJG2gilcH0oc2YPjS7EH2hsLqJYSocOonUhAgiZxiGCYKmiYKFOIBr/5U7ZtKgY12F3CuBmcOasUeIBfvPj5mBC5aNwQFGHcVcCACzR7RigIc1hikeh84agmGttThjcXtB1rR/n70TLttzPC5YNqbgPtGpS9UlmgCHZt4sNqy+Z5gKJ8KCHMMwFQjLceXNNftPxiEzBmP6sPBWhDtPmYuL/vRyj9eiFELgx0dMQ9cvn8X9b6zy/btdxvXFLuP8xfj5yz7Ig7xQRvapx8MXLAYAHH7Lk6HbGdOvV1Z207BoPixyjuLx3ZgJni1yDFPhUG1QTZx1MwzDVAZeC6DDZnF69nKhJh7BvJG9CyppM2t4Cx46fxH2CllMvnCKu4Cuq4pix1G9MbCpBofMzF9CSpU0hQnH4+/ljknsKahl8H9vr867/7z2/Il8wsKrPoapcITDIse6GYZhKgMvPfZRc/KnoGcYv3SHHHXH8bOQkf6SZnBN3uISiwhHce1SQdddL+UokXLL0TNw76sru9U9mVd9DFPh0HdJmEKrDMMwpcDLIleMjHIMY9IdS34hhO9xyplPi8t/zlkIAJhl1AssFX6nqSXj++IHB09Ba333ZRTnEcYwFQ59ofBLg2GYSsErtIQFOaaYlNq18YeHTEFUEzh5pxEl7ce2wrDedXj1ymX4/clzStoPOk99Y8/xJewJu1YyTMVDrXCcPIBhmErBK2tlMdKLM4xJqZ3w5o/sjVeuWIaaOHvLFIv6qtKLLnSWGtu/OAlUwsLqe4apcOgLgt3xGYapFLxENrbIMcWkHN6JLMRte9A4vVKHtFSEICeEuF0IIXP8G0j2nSeEeFQIsVUI8bkQ4gYhRFbBGyFElRDiWiHEZ0KIDiHEk0KIXRTH99Umw5SCmGY/xmXwzmIYhvGFl8ymsSDHFBF+JzLdQVcqbX0uddmn0tsn/XEzgPtd2wSAmwCskFJ+CgBCiCkAHgDwGoBzAQwCcD6AEQD2cv3+dgAHALgewLsAjgVwrxBioZTyCesgwdpkmB6nsSZmfR7eu66EPWEYhvGPl2tlnON8mSJS6hg5ZtukixT4ZkHOB4Zg9QTdJoRYAKAWwG/I5qsBrAGwSEq52dhvBYBbhBA7SykfNLbNAnAogHOklNcb2+4A8CqAawHsFLRNhikVjbUx/PSIaVi7NYHpQ8MXbmUYhulJvIxv1VxChWGYMidBBbkSu85W8ox5OHSr+W8BQAjRAGAJgDtMgcvgDgCbARxMth0IIAngVnODlLITwM8BLBBC9A/RJsOUjOWT+uOI2Vx/iWGYCsJlkZs0sBG9qmOKnRkmONQgN6pPfek6wmxTJNK2IFfqGLmKsMi5EULEoAtRj0spVxibJ0E/n2fpvlLKhBDiRQBTyeapAN50CWcA8DR0l80pAFYGbJNhGIZhGJ9Qi9ytR8/AruP7lq4zzDYJjWX646lzcf3972D5xH4l7BGzLUAtcqX2IqhIQQ7AMgCtcLpV9jf+X+mx/0oAc137fqrYDwAGhGjTQgix3ms7oTHP9wzDMAyzTSNI3krOVsl0B+1t9XhmxToAQFNtHFfsPaHEPWK2BWiMXKnjeitVkDscumvknWRbjfF/l8f+neR7c1/VfrStIG0yDMMwDOMTKrtxtkqmO7hot7HoTKaxbAJb4Zjikc7YPrteSZt6kooT5IQQ9QD2AfBvKeUa8lWH8X+Vx8+qyffmvqr9aFtB2rSQUjZ5bTcxLHZslWMYhmG2W+j6J1LixRCzbdJcF8f1h3IUDLPtUonJTvZFdrZKwHZ/7I9s+gP4zLWvaj+QfYO0yTAMwzCMT6gmW6vE1QjDMEyJqcSp8wjoGSPvcW1/FUAKwAy6UQgRh5685EWy+UUAYw3rHmW28f9LIdpkGIZhGCYEGlvkGIZhAlNRgpwQog3ArgD+LKXcSr+TUm6AXjT8KJeAdhSAegB/JNvuAhADcCJpuwrAcQAek1J+FqJNhmEYhmH8QlLDc7IThmGY4FRajNwh0Pvsdqs0uRTA4wAeFkLcCmAQgPMA3CulvN/cSUr5lBDijwCuM2rGvQfgGABDARwbpk2GYRiGYfwjiSTHchzDMExwKsoiB92t8gvoVrIspJTPQ7fYdQH4IYCTANwC4CCP3Y8GcIPx/4+gW+h2l1I+VkCbDMMwDMP4gBZrZtdKhmEqhZuOnI54VMPle40vdVcqyyInpfSs2+ba51EA833s1wngAuNfUdpkGIZhGMYfRI5jQY5hmIpht4n98NqVyxArcQ05oPIscgzDMAzDbANIjpFjGKZCKQchDmBBjmEYhmGYEkBj5NggxzAMExwW5BiGYRiG6XHYIscwDFMYLMgxDMMwDNPjcIwcwzBMYbAgxzAMwzBMjyMlLT/AghzDMExQWJBjGIZhGKbHWbWx0/q8sTNZwp4wDMNUJizIMQzDMAzT45yysN36PL5/Qwl7wjAMU5lUVB05hmEYhmG2DRqqY3j728sBAPEo65UZhmGCwoIcwzAMwzAlgQU4hmGY8PAMyjAMwzAMwzAMU2GwIMcwDMMwDMMwDFNhsCDHMAzDMAzDMAxTYbAgxzAMwzAMwzAMU2GwIMcwDMMwDMMwDFNhsCDHMAzDMAzDMAxTYbAgxzAMwzAMwzAMU2GwIMcwDMMwDMMwDFNhsCDHMAzDMAzDMAxTYbAgxzAMwzAMwzAMU2GwIMcwDMMwDMMwDFNhsCDHMAzDMAzDMAxTYbAgxzAMwzAMwzAMU2EIKWWp+7DdIYTIABCNjY2l7grDMAzDMAzDMGXIhg0bAEBKKT2NbyzIlQAhhHnRN5S0I07qjf83l7QX2XC/gmFqB8ppbAHleb3KsU9A+fYLKM/xVa7Xi/sVjHIcW0B5Xq9y7BNQvv0CynN8lev14n4Fo7vHViMASCmF15fRbjookxtTvG4qcT8shBAPA4CUclFpe+KE+xUMIcR6oLzGFlCe16sc+wSUb7+A8hxf5Xq9uF/BKMexBZTn9SrHPgHl2y+gPMdXuV4v7lcwuntsme2r4Bg5hmEYhmEYhmGYCoMFOYZhGIZhGIZhmAqDBTmGYRiGYRiGYZgKgwU5hmEYhmEYhmGYCoOzVpaAcgy6ZbYNeGwx3QmPL6a74LHFdCc8vpjuoqeSnajaZ4scwzAMwzAMwzBMhcGCHMMwDMMwDMMwTIXBrpUMwzAMwzAMwzAVBlvkGIZhGIZhGIZhKgwW5BiGYRiGYRiGYSoMFuQYhmEYhmEYhmEqDBbkGIZhGIZhGIZhKgwW5HwihJgphPixEOJ1IcQWIcRHQojfCyFGeuw7TwjxqBBiqxDicyHEDUKIWtc+/YUQ1wghHhJCbBJCSCHEohzH31sI8bwQotM49uVCiGjxz5QpBaUcX0KIU4UQdwohPjT2u71bTpIpCaUaW0KIViHEBUKIR4QQq4UQ64UQTwghDuq+s2V6mhKOLyGEuFkI8bIxtjYLIV4SQpwphIh13xkzPUWp113kd0ONdqUQYkrRTpApGSVec60wvnf/uybMubAg4J+LAMwH8EcALwPoB+ArAF4QQsySUr4BAMZD/gCA1wCcC2AQgPMBjACwF2lvjNHmu0Z781QHFkIsB/AXAA8C+CqASQC+AaC38TdT+ZRsfAH4GoAGAE8bx2W2LUo1tuYCuArAPwF8G0AKwAEA7hRCfENK+a3inSJTQko1vjQA0wDcB+AD6ONrLoDrAcwAcHSRzo8pHaV8L1K+ByBT4Lkw5UWpx9Zz0OcqyquhzkRKyf98/DNuSty1bRSATgC3k23/BPAJgHqy7UQAEsDOZFsvAK3G532N7xcpjv2acdMjZNu3AaQBjCr1teF/FT++hsIuRbKeHo//Vf6/Uo0tAMMBDHVtE9BfilsB1JT62vC/yh1fOfrzI+iL7rZSXxv+V/ljC8AiAF3GmksCmFLq68L/KntsAVgB4C/FOhd2rfSJlPJxKWXCte0d6ELWOAAQQjQAWALgDinlZrLrHQA2AziY/HaTlHJNvuMKIcYDGA/gZillmnz1E+gayQPCnRFTTpRqfBn7fiiN2YXZ9ijV2JJSfiCl/NC1TUL3LqgBMCzM+TDlRSnnLgUfQlcYNBbQBlMGlHpsCSEiAG4AcCN0SwuzjVDqsWW0X+V20QwDC3IFIIQQAPoC+NLYNAm6u+qzdD9jsLwIYGqIw5i/cbf5GXQtQZg2mQqgh8YXsx1S4rFluu9+mXMvpmLpyfElhIgJIXoLIQYLIfaD7vb0PnR3S2Ybo4fnrlMADATAbuDbAT08tpYC2AJgixDiPSHEyWEbYkGuMI6A/pDfafzd3/h/pce+KwEMCHGM7miTqQx6Ynwx2yclGVtCiBbobikPSylXF6NNpizpyfG1DMBqAB8BuBu6gnMflwcLs+3QI2PLmKu+BeAKKeX6MG0wFUdPzVsvA7gcukfdSdAFx5uFEF8L0xgnOwmJEGIsgB8DeBTAr4zNNcb/XR4/6STfByFfmwWbZZnyowfHF7OdUaqxJYTQAPwGusvbmYW2x5QnJRhfT0J3f2oEsDOAKQDqC2iPKVN6eGx9E8AXAG4K+XumgujJsSWl3Nt17F8Yx71MCPFTKeWGIO2xRS4EQoh+AP4BYB2Ag6SUZjajDuP/Ko+fVZPvg9AdbTJlTA+PL2Y7osRj6/+gW0+Ok1K+UoT2mDKjFONLSvmllPJ+KeWfpJRnAPgrgP8YfWG2EXpybAkhJgI4FcB5UspUiO4yFUSp11yG98D10A0zc4P+ngW5gAghGgHcC137t0xK+Tn52jS/9s/6ob7tsxCH7I42mTKlBOOL2U4o5dgSQlwO4HQAF0opf1dIW0x5UkZz113QLXL7FLFNpoSUYGxdDeB5AK8LIYYJIYZBL/cEAAOEEINDtMmUIWU0b31s/N8S9IcsyAVACFEN4G8ARgPYU0r5lmuXV6HXspnh+l0curvHiyEOa/7G3eYA6PUswrTJlCElGl/MdkApx5YQ4gwAVwD4oZTye2HbYcqXMpu7THcnzlq5DVCisTUEwEzoCXPMf981vvsHgGdCtMmUGWU2b40w/g8cO86CnE+MNLR/gG72PEhK+aR7H8Ov9X4ARwkhqI/+UdA1hH8Melwp5WsA3gRwstEHk9Og18r5U9A2mfKjVOOL2fYp5dgSQhwCva7XbwCcF6YNprwp1fgSQrS43okmJxr/Pxe0Taa8KOHcdQ6A/Vz//s/47lwAx4ZokykjSjxvaa5t1QAuALAJwBNB2+RkJ/75PoC9oUvvLUKII8l3m6WUfzE+XwrgcQAPCyFuhW41Ow/AvVLK+2mDQoivGx/HGf8fJYRYAGC9lPJGsusFAO4B8G8hxB8ATIRegf5mKeXbxTpBpqSUbHwJIfYCsIPxZxWAyeS3v3LXAmMqjpKMLSHELOj1dtZALwJ+hJ7d2eI/UspVxTlFpoSUau7aG8DXhRB3A3gPQB30lN7LAPxDSvlAEc+RKQ0lGVtSyofcHRFCNBkfH5JSvljgeTGlp5Tz1qVCiLugFwZvBXAMdKvgaa56df6QRaosvq3/A/Aw9ErtXv9WuPZdAOAx6IGQq6BrpOs82vTVnrQrxb8APVPOxwCuBBAt9XXhf5U/vgDcnmPfRaW+NvyvMscWdK21aj8eW9vIvxKOr4kAfgvd7a0Dek2m56EvsmKlvi78r3LHlqIv5nw2pdTXhf9V7tgCMB268PgJ9GyYG42+7Bn2XITRMMMwDMMwDMMwDFMhcIwcwzAMwzAMwzBMhcGCHMMwDMMwDMMwTIXBghzDMAzDMAzDMEyFwYIcwzAMwzAMwzBMhcGCHMMwDMMwDMMwTIXBghzDMAzDMAzDMEyFwYIcwzAMwzAMwzBMhcGCHMMwDMN0I0KI24UQXLSVYRiGKSrRUneAYRiGYSqJgELZ8G7rCMMwDLNdI6RkJSHDMAzD+EUIcaRr044ATgbwMwCPuL77M4AEgIiUsrMHuscwDMNsJ7BFjmEYhmECIKX8Nf1bCBGFLsg94f6OkOz2jjEMwzDbFRwjxzAMwzDdiFeMnLlNCNFqfP5SCLFJCPEXIUQ/Y5+ThRBvCCE6hRBvCiH2UbR/iBDiUeP3W4UQTwkhDuyJc2MYhmFKBwtyDMMwDFM6/gWgEcA3ANwCYE8AfxZCXADgAgC/BPA1AHEAdwkhHDF3QohvA/g9gE0ALjP23Qrgj0KIM3rqJBiGYZieh10rGYZhGKZ0PC2ltAQuIQQAnANgIICJUsqNxvYHAbwE3YXzYmPbNACXAviOlPIS0uaPhBB/AfAdIcQdUspNPXEiDMMwTM/CFjmGYRiGKR3Xu/42k6XcYQpxACClfBnARgCjyL5HAJAAfimE6E3/AbgHQC8Ac7ut5wzDMExJYYscwzAMw5SO911/rzP+/8Bj33UAWsnf4wAIAG/maL9v+K4xDMMw5QwLcgzDMAxTIqSUacVXqu3C9VkCWJ5j/9dCdo1hGIYpc1iQYxiGYZjK5B0AuwH4SEr5Rqk7wzAMw/QsHCPHMAzDMJXJr4z/rxZCRNxfCiHYrZJhGGYbhi1yDMMwDFOBSCmfEUJcAeAKAC8KIf4I4DMA/QFMB7A79LIFDMMwzDYIC3IMwzAMU6FIKa8UQjwL4EwAZwOoA/AFgFeNbQzDMMw2ipBSlroPDMMwDMMwDMMwTAA4Ro5hGIZhGIZhGKbCYEGOYRiGYRiGYRimwmBBjmEYhmEYhmEYpsJgQY5hGIZhGIZhGKbCYEGOYRiGYRiGYRimwmBBjmEYhmEYhmEYpsJgQY5hGIZhGIZhGKbCYEGOYRiGYRiGYRimwmBBjmEYhmEYhmEYpsJgQY5hGIZhGIZhGKbC+H+mYapNdUijHQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.filter(\n",
    "    regex=\"demand_.*?_mean\", # `.*?` means any number of any characters.\n",
    "    axis=1  # Filter by column names.\n",
    ").plot(figsize=[14, 7])\n",
    "\n",
    "ax.set_title(\"Rolling window mean of electricity demand\")\n",
    "ax.set_ylabel(\"Electricity demand\")\n",
    "ax.set_xlabel(\"Time\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e40c40b-904a-45dd-9100-dbbb70efed0c",
   "metadata": {},
   "source": [
    "We can see how different window sizes have smoothed over different seasonalities. This allows the model to make use of behaviours seen at different time scales (e.g., if the daily average of the demand is greater than the average of the past year then perhaps this can influence future values of our target variable)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ed053f9-e3de-489f-8355-6883d0a8311a",
   "metadata": {},
   "source": [
    "# Using sktime"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "396360ff-fde7-4ab3-8a51-831a87c532f2",
   "metadata": {},
   "source": [
    "Let's see how we can extract window features using the sktime library."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4c4d5d68-55d8-4ad1-861c-f150ad845161",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sktime.transformations.series.summarize import WindowSummarizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5212c2c2-da44-48c3-aea4-73625ff2bbe0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "81c91000-ac0b-4931-8ed9-daacf8392bfa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand_lag_1</th>\n",
       "      <th>demand_lag_2</th>\n",
       "      <th>demand_lag_3</th>\n",
       "      <th>demand_mean_1_24</th>\n",
       "      <th>demand_mean_1_168</th>\n",
       "      <th>demand_std_1_24</th>\n",
       "      <th>demand_std_3_168</th>\n",
       "      <th>demand_mad_1_12</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-01 00:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 01:00:00</th>\n",
       "      <td>8314.448682</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 02:00:00</th>\n",
       "      <td>8267.187296</td>\n",
       "      <td>8314.448682</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 03:00:00</th>\n",
       "      <td>7394.528444</td>\n",
       "      <td>8267.187296</td>\n",
       "      <td>8314.448682</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01 04:00:00</th>\n",
       "      <td>6952.047520</td>\n",
       "      <td>7394.528444</td>\n",
       "      <td>8267.187296</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 19:00:00</th>\n",
       "      <td>9979.909902</td>\n",
       "      <td>10258.585392</td>\n",
       "      <td>10019.921572</td>\n",
       "      <td>8802.565712</td>\n",
       "      <td>9670.463454</td>\n",
       "      <td>974.759690</td>\n",
       "      <td>1583.199789</td>\n",
       "      <td>277.824899</td>\n",
       "      <td>28.350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 20:00:00</th>\n",
       "      <td>9596.777060</td>\n",
       "      <td>9979.909902</td>\n",
       "      <td>10258.585392</td>\n",
       "      <td>8786.593557</td>\n",
       "      <td>9654.616819</td>\n",
       "      <td>957.615692</td>\n",
       "      <td>1558.917200</td>\n",
       "      <td>223.694120</td>\n",
       "      <td>22.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 21:00:00</th>\n",
       "      <td>8883.230296</td>\n",
       "      <td>9596.777060</td>\n",
       "      <td>9979.909902</td>\n",
       "      <td>8764.566712</td>\n",
       "      <td>9638.018555</td>\n",
       "      <td>948.645664</td>\n",
       "      <td>1539.992921</td>\n",
       "      <td>223.694120</td>\n",
       "      <td>18.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 22:00:00</th>\n",
       "      <td>8320.260550</td>\n",
       "      <td>8883.230296</td>\n",
       "      <td>9596.777060</td>\n",
       "      <td>8750.681279</td>\n",
       "      <td>9624.108291</td>\n",
       "      <td>952.771813</td>\n",
       "      <td>1526.838185</td>\n",
       "      <td>223.694120</td>\n",
       "      <td>18.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-02-28 23:00:00</th>\n",
       "      <td>8110.055916</td>\n",
       "      <td>8320.260550</td>\n",
       "      <td>8883.230296</td>\n",
       "      <td>8744.571813</td>\n",
       "      <td>9613.687286</td>\n",
       "      <td>956.539865</td>\n",
       "      <td>1519.920008</td>\n",
       "      <td>399.583676</td>\n",
       "      <td>18.900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45240 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     demand_lag_1  demand_lag_2  demand_lag_3  \\\n",
       "date_time                                                       \n",
       "2010-01-01 00:00:00           NaN           NaN           NaN   \n",
       "2010-01-01 01:00:00   8314.448682           NaN           NaN   \n",
       "2010-01-01 02:00:00   8267.187296   8314.448682           NaN   \n",
       "2010-01-01 03:00:00   7394.528444   8267.187296   8314.448682   \n",
       "2010-01-01 04:00:00   6952.047520   7394.528444   8267.187296   \n",
       "...                           ...           ...           ...   \n",
       "2015-02-28 19:00:00   9979.909902  10258.585392  10019.921572   \n",
       "2015-02-28 20:00:00   9596.777060   9979.909902  10258.585392   \n",
       "2015-02-28 21:00:00   8883.230296   9596.777060   9979.909902   \n",
       "2015-02-28 22:00:00   8320.260550   8883.230296   9596.777060   \n",
       "2015-02-28 23:00:00   8110.055916   8320.260550   8883.230296   \n",
       "\n",
       "                     demand_mean_1_24  demand_mean_1_168  demand_std_1_24  \\\n",
       "date_time                                                                   \n",
       "2010-01-01 00:00:00               NaN                NaN              NaN   \n",
       "2010-01-01 01:00:00               NaN                NaN              NaN   \n",
       "2010-01-01 02:00:00               NaN                NaN              NaN   \n",
       "2010-01-01 03:00:00               NaN                NaN              NaN   \n",
       "2010-01-01 04:00:00               NaN                NaN              NaN   \n",
       "...                               ...                ...              ...   \n",
       "2015-02-28 19:00:00       8802.565712        9670.463454       974.759690   \n",
       "2015-02-28 20:00:00       8786.593557        9654.616819       957.615692   \n",
       "2015-02-28 21:00:00       8764.566712        9638.018555       948.645664   \n",
       "2015-02-28 22:00:00       8750.681279        9624.108291       952.771813   \n",
       "2015-02-28 23:00:00       8744.571813        9613.687286       956.539865   \n",
       "\n",
       "                     demand_std_3_168  demand_mad_1_12  temperature  \n",
       "date_time                                                            \n",
       "2010-01-01 00:00:00               NaN              NaN       21.525  \n",
       "2010-01-01 01:00:00               NaN              NaN       22.400  \n",
       "2010-01-01 02:00:00               NaN              NaN       22.150  \n",
       "2010-01-01 03:00:00               NaN              NaN       21.800  \n",
       "2010-01-01 04:00:00               NaN              NaN       20.250  \n",
       "...                               ...              ...          ...  \n",
       "2015-02-28 19:00:00       1583.199789       277.824899       28.350  \n",
       "2015-02-28 20:00:00       1558.917200       223.694120       22.200  \n",
       "2015-02-28 21:00:00       1539.992921       223.694120       18.900  \n",
       "2015-02-28 22:00:00       1526.838185       223.694120       18.900  \n",
       "2015-02-28 23:00:00       1519.920008       399.583676       18.900  \n",
       "\n",
       "[45240 rows x 9 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transformer = WindowSummarizer(\n",
    "    lag_feature={\n",
    "        \"lag\": [1, 2, 3],  # Lag features.\n",
    "        \"mean\": [[1, 24], [1, 24*7]],  # [[lag, window size]]\n",
    "        \"std\": [[1, 24], [3, 24*7]],\n",
    "        mad: [[1, 12]],  # Can pass custom functions.\n",
    "    },\n",
    "    target_cols=[\"demand\"],\n",
    ")\n",
    "\n",
    "result = transformer.fit_transform(df)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "134d5a50-6e87-4384-9944-c18bb68c84ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>demand_lag_1</th>\n",
       "      <th>demand_lag_2</th>\n",
       "      <th>demand_lag_3</th>\n",
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       "      <th>demand_mad_1_12</th>\n",
       "      <th>temperature</th>\n",
       "      <th>demand</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>6867.199634</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <th>2015-02-28 19:00:00</th>\n",
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       "      <td>10019.921572</td>\n",
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       "      <td>22.200</td>\n",
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       "    <tr>\n",
       "      <th>2015-02-28 21:00:00</th>\n",
       "      <td>8883.230296</td>\n",
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       "    <tr>\n",
       "      <th>2015-02-28 22:00:00</th>\n",
       "      <td>8320.260550</td>\n",
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       "      <th>2015-02-28 23:00:00</th>\n",
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      ],
      "text/plain": [
       "                     demand_lag_1  demand_lag_2  demand_lag_3  \\\n",
       "date_time                                                       \n",
       "2010-01-01 00:00:00           NaN           NaN           NaN   \n",
       "2010-01-01 01:00:00   8314.448682           NaN           NaN   \n",
       "2010-01-01 02:00:00   8267.187296   8314.448682           NaN   \n",
       "2010-01-01 03:00:00   7394.528444   8267.187296   8314.448682   \n",
       "2010-01-01 04:00:00   6952.047520   7394.528444   8267.187296   \n",
       "...                           ...           ...           ...   \n",
       "2015-02-28 19:00:00   9979.909902  10258.585392  10019.921572   \n",
       "2015-02-28 20:00:00   9596.777060   9979.909902  10258.585392   \n",
       "2015-02-28 21:00:00   8883.230296   9596.777060   9979.909902   \n",
       "2015-02-28 22:00:00   8320.260550   8883.230296   9596.777060   \n",
       "2015-02-28 23:00:00   8110.055916   8320.260550   8883.230296   \n",
       "\n",
       "                     demand_mean_1_24  demand_mean_1_168  demand_std_1_24  \\\n",
       "date_time                                                                   \n",
       "2010-01-01 00:00:00               NaN                NaN              NaN   \n",
       "2010-01-01 01:00:00               NaN                NaN              NaN   \n",
       "2010-01-01 02:00:00               NaN                NaN              NaN   \n",
       "2010-01-01 03:00:00               NaN                NaN              NaN   \n",
       "2010-01-01 04:00:00               NaN                NaN              NaN   \n",
       "...                               ...                ...              ...   \n",
       "2015-02-28 19:00:00       8802.565712        9670.463454       974.759690   \n",
       "2015-02-28 20:00:00       8786.593557        9654.616819       957.615692   \n",
       "2015-02-28 21:00:00       8764.566712        9638.018555       948.645664   \n",
       "2015-02-28 22:00:00       8750.681279        9624.108291       952.771813   \n",
       "2015-02-28 23:00:00       8744.571813        9613.687286       956.539865   \n",
       "\n",
       "                     demand_std_3_168  demand_mad_1_12  temperature  \\\n",
       "date_time                                                             \n",
       "2010-01-01 00:00:00               NaN              NaN       21.525   \n",
       "2010-01-01 01:00:00               NaN              NaN       22.400   \n",
       "2010-01-01 02:00:00               NaN              NaN       22.150   \n",
       "2010-01-01 03:00:00               NaN              NaN       21.800   \n",
       "2010-01-01 04:00:00               NaN              NaN       20.250   \n",
       "...                               ...              ...          ...   \n",
       "2015-02-28 19:00:00       1583.199789       277.824899       28.350   \n",
       "2015-02-28 20:00:00       1558.917200       223.694120       22.200   \n",
       "2015-02-28 21:00:00       1539.992921       223.694120       18.900   \n",
       "2015-02-28 22:00:00       1526.838185       223.694120       18.900   \n",
       "2015-02-28 23:00:00       1519.920008       399.583676       18.900   \n",
       "\n",
       "                          demand  \n",
       "date_time                         \n",
       "2010-01-01 00:00:00  8314.448682  \n",
       "2010-01-01 01:00:00  8267.187296  \n",
       "2010-01-01 02:00:00  7394.528444  \n",
       "2010-01-01 03:00:00  6952.047520  \n",
       "2010-01-01 04:00:00  6867.199634  \n",
       "...                          ...  \n",
       "2015-02-28 19:00:00  9596.777060  \n",
       "2015-02-28 20:00:00  8883.230296  \n",
       "2015-02-28 21:00:00  8320.260550  \n",
       "2015-02-28 22:00:00  8110.055916  \n",
       "2015-02-28 23:00:00  8519.368752  \n",
       "\n",
       "[45240 rows x 10 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = result.join(df[\"demand\"], how=\"left\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84cdbb49-e3cc-4003-a9ca-d6698c891a7c",
   "metadata": {},
   "source": [
    "So now we've shown how to create rolling window features using different libraries. "
   ]
  }
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